Awesome-FL

Federated Learning Resources

Table of Contents

Papers
- FL in top-tier journal
- FL in top-tier conference and journal by category
  - AI ML DM Secure CV NLP IR DB Network System Others
- FL on Graph Data and Graph Neural Networks
- FL on Tabular Data
Framework
Datasets
Surveys
Tutorials and Courses
Key Conferences/Workshops/Journals
- Workshops Special Issues Special Tracks
Update log
Acknowledgments
Citation

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More items will be added to the repository. Please feel free to suggest other key resources by opening an issue report, submitting a pull request, or dropping me an email @ (im.young@foxmail.com). If you want to communicate with more friends in the field of federated learning, please join the QQ group [联邦学习交流群], the group number is 833638275. Enjoy reading!

papers

categories

Artificial Intelligence (IJCAI, AAAI, AISTATS, ALT, AI)
Machine Learning (NeurIPS, ICML, ICLR, COLT, UAI, Machine Learning, JMLR, TPAMI)
Data Mining (KDD, WSDM)
Secure (S&P, CCS, USENIX Security, NDSS)
Computer Vision (ICCV, CVPR, ECCV, MM, IJCV)
Natural Language Processing (ACL, EMNLP, NAACL, COLING)
Information Retrieval (SIGIR)
Database (SIGMOD, ICDE, VLDB)
Network (SIGCOMM, INFOCOM, MOBICOM, NSDI, WWW)
System (OSDI, SOSP, ISCA, MLSys, EuroSys, TPDS, DAC, TOCS, TOS, TCAD, TC)
Others (ICSE, FOCS, STOC)

Events

Venue	2023-2020	before 2020
IJCAI	23, 22, 21, 20	19
AAAI	24, 23, 22, 21, 20	-
AISTATS	23, 22, 21, 20	-
ALT	22	-
AI (J)	-	-
NeurIPS	23, 22, 21, 20	18, 17
ICML	23, 22, 21, 20	19
ICLR	24, 23, 22, 21, 20	-
COLT	23	-
UAI	23, 22, 21	-
Machine Learning (J)	24, 23, 22	-
JMLR (J)	23, 22	-
TPAMI (J)	23, 22	-
KDD	23, 22, 21, 20
WSDM	24, 23, 22, 21	19
S&P	23, 22	19
CCS	23, 22, 21, 19	17
USENIX Security	23, 22, 20	-
NDSS	23, 22, 21	-
CVPR	23, 22, 21	-
ICCV	23,21	-
ECCV	22, 20	-
MM	23, 22, 21, 20	-
IJCV (J)	-	-
ACL	23, 22, 21	19
NAACL	22, 21	-
EMNLP	23, 22, 21, 20	-
COLING	20	-
SIGIR	23, 22, 21, 20	-
SIGMOD	22, 21	-
ICDE	23, 22, 21	-
VLDB	23, 22, 21, 21, 20	-
SIGCOMM	-	-
INFOCOM	23, 22, 21, 20	19, 18
MobiCom	23, 22, 21, 20
NSDI	23(1, 2)	-
WWW	23, 22, 21
OSDI	21	-
SOSP	21	-
ISCA	-	-
MLSys	23, 22, 20	19
EuroSys	23, 22, 21, 20
TPDS (J)	23, 22, 21, 20	-
DAC	22, 21	-
TOCS	-	-
TOS	-	-
TCAD	23, 22, 21	-
TC	23, 22, 21	-
ICSE	23, 21	-
FOCS	-	-
STOC	-	-

keywords

Statistics: code is available & stars >= 100 | citation >= 50 | Top-tier venue

kg.: Knowledge Graph | data.: dataset | surv.: survey

fl in top-tier journal

Papers of federated learning in Nature(and its sub-journals), Cell, Science(and Science Advances) and PANS refers to WOS search engine.

fl in top-tier journal

Title	Affiliation	Venue	Year	Materials
PPML-Omics: A privacy-preserving federated machine learning method protects patients’ privacy in omic data	KAUST	Science Advances	2024	[PUB] [CODE]
Federated learning is not a cure-all for data ethics	TUM; UvA	Nat. Mach. Intell.(Comment)	2024	[PUB]
Robustly federated learning model for identifying high-risk patients with postoperative gastric cancer recurrence	Jiangmen Central Hospital; Guilin University of Aerospace Technology; Guilin University of Electronic Technology;	Nat. Commun.	2024	[PUB] [CODE]
Selective knowledge sharing for privacy-preserving federated distillation without a good teacher	HKUST	Nat. Commun.	2024	[PUB] [PDF] [CODE]
A federated learning system for precision oncology in Europe: DigiONE	IQVIA Cancer Research BV	Nat. Med. (Comment)	2024	[PUB]
Multi-client distributed blind quantum computation with the Qline architecture	Sapienza Università di Roma	Nat. Commun.	2023	[PUB] [PDF]
Device-independent quantum randomness–enhanced zero-knowledge proof	USTC	PNAS	2023	[PUB] [PDF] [新闻]
Collaborative and privacy-preserving retired battery sorting for profitable direct recycling via federated machine learning	Tsinghua University	Nat. Commun.	2023	[PUB]
Advocating for neurodata privacy and neurotechnology regulation	Columbia University	Nat. Protoc. (Perspective)	2023	[PUB]
Federated benchmarking of medical artificial intelligence with MedPerf	IHU Strasbourg; University of Strasbourg; Dana-Farber Cancer Institute; Weill Cornell Medicine; Harvard T.H. Chan School of Public Health; MIT; Intel	Nat. Mach. Intell.	2023	[PUB] [PDF] [CODE]
Algorithmic fairness in artificial intelligence for medicine and healthcare	Harvard Medical School; Broad Institute of Harvard and Massachusetts Institute of Technology; Dana-Farber Cancer Institute	Nat. Biomed. Eng. (Perspective)	2023	[PUB] [PDF]
Differentially private knowledge transfer for federated learning	THU	Nat. Commun.	2023	[PUB] [CODE]
Decentralized federated learning through proxy model sharing	Layer 6 AI; University of Waterloo; Vector Institute	Nat. Commun.	2023	[PUB] [PDF] [CODE]
Federated machine learning in data-protection-compliant research	University of Hamburg	Nat. Mach. Intell.(Comment)	2023	[PUB]
Federated learning for predicting histological response to neoadjuvant chemotherapy in triple-negative breast cancer	Owkin	Nat. Med.	2023	[PUB] [CODE]
Federated learning enables big data for rare cancer boundary detection	University of Pennsylvania	Nat. Commun.	2022	[PUB] [PDF] [CODE]
Federated learning and Indigenous genomic data sovereignty	Hugging Face	Nat. Mach. Intell. (Comment)	2022	[PUB]
Federated disentangled representation learning for unsupervised brain anomaly detection	TUM	Nat. Mach. Intell.	2022	[PUB] [PDF] [CODE]
Shifting machine learning for healthcare from development to deployment and from models to data	Stanford University; Greenstone Biosciences	Nat. Biomed. Eng. (Review Article)	2022	[PUB]
A federated graph neural network framework for privacy-preserving personalization	THU	Nat. Commun.	2022	[PUB] [CODE] [解读]
Communication-efficient federated learning via knowledge distillation	THU	Nat. Commun.	2022	[PUB] [PDF] [CODE]
Lead federated neuromorphic learning for wireless edge artificial intelligence	XMU; NTU	Nat. Commun.	2022	[PUB] [CODE] [解读]
A novel decentralized federated learning approach to train on globally distributed, poor quality, and protected private medical data	University of Wollongong	Sci. Rep.	2022	[PUB]
Advancing COVID-19 diagnosis with privacy-preserving collaboration in artificial intelligence	HUST	Nat. Mach. Intell.	2021	[PUB] [PDF] [CODE]
Federated learning for predicting clinical outcomes in patients with COVID-19	MGH radiology and Harvard Medical School	Nat. Med.	2021	[PUB] [CODE]
Adversarial interference and its mitigations in privacy-preserving collaborative machine learning	Imperial College London; TUM; OpenMined	Nat. Mach. Intell.(Perspective)	2021	[PUB]
Swarm Learning for decentralized and confidential clinical machine learning	DZNE; University of Bonn;	Nature	2021	[PUB] [CODE] [SOFTWARE] [解读]
End-to-end privacy preserving deep learning on multi-institutional medical imaging	TUM; Imperial College London; OpenMined	Nat. Mach. Intell.	2021	[PUB] [CODE] [解读]
Communication-efficient federated learning	CUHK; Princeton University	PANS.	2021	[PUB] [CODE]
Breaking medical data sharing boundaries by using synthesized radiographs	RWTH Aachen University	Science. Advances.	2020	[PUB] [CODE]
Secure, privacy-preserving and federated machine learning in medical imaging	TUM; Imperial College London; OpenMined	Nat. Mach. Intell.(Perspective)	2020	[PUB]

fl in top ai conference and journal

Federated Learning papers accepted by top AI(Artificial Intelligence) conference and journal, Including IJCAI(International Joint Conference on Artificial Intelligence), AAAI(AAAI Conference on Artificial Intelligence), AISTATS(Artificial Intelligence and Statistics), ALT(International Conference on Algorithmic Learning Theory), AI(Artificial Intelligence).

fl in top ai conference and journal

Title	Affiliation	Venue	Year	Materials
FedMut: Generalized Federated Learning via Stochastic Mutation	NTU	AAAI	2024	[PUB]
Federated Partial Label Learning with Local-Adaptive Augmentation and Regularization	Carleton University	AAAI	2024	[PUB] [PAGE]
No Prejudice! Fair Federated Graph Neural Networks for Personalized Recommendation	IIT	AAAI	2024	[PUB] [PAGE] [PDF] [CODE]
Formal Logic Enabled Personalized Federated Learning through Property Inference	Vanderbilt University	AAAI	2024	[PUB] [PDF]
Task-Agnostic Privacy-Preserving Representation Learning for Federated Learning against Attribute Inference Attacks	Illinois Tech	AAAI	2024	[PUB] [PAGE] [PDF] [CODE]
FairTrade: Achieving Pareto-Optimal Trade-Offs between Balanced Accuracy and Fairness in Federated Learning	Leibniz University	AAAI	2024	[PUB] [PAGE]
Combating Data Imbalances in Federated Semi-supervised Learning with Dual Regulators	HKUST	AAAI	2024	[PUB] [PAGE] [PDF]
Fed-QSSL: A Framework for Personalized Federated Learning under Bitwidth and Data Heterogeneity	UT	AAAI	2024	[PUB] [PAGE] [PDF]
On Disentanglement of Asymmetrical Knowledge Transfer for Modality-Task Agnostic Federated Learning	University of Virginia	AAAI	2024	[PUB]
FedDAT: An Approach for Foundation Model Finetuning in Multi-Modal Heterogeneous Federated Learning	LMU Munich Siemens AG	AAAI	2024	[PUB] [PAGE] [PDF] [CODE]
Watch Your Head: Assembling Projection Heads to Save the Reliability of Federated Models	Xi'an Jiaotong University Shaanxi Joint Key Laboratory for Artificial Intelligence	AAAI	2024	[PUB] [PAGE] [PDF]
FedGCR: Achieving Performance and Fairness for Federated Learning with Distinct Client Types via Group Customization and Reweighting	NTU	AAAI	2024	[PUB] [PAGE] [CODE]
Federated Modality-Specific Encoders and Multimodal Anchors for Personalized Brain Tumor Segmentation	Xiamen University	AAAI	2024	[PUB] [PAGE] [PDF] [CODE]
Exploiting Label Skews in Federated Learning with Model Concatenation	NUS	AAAI	2024	[PUB] [PAGE] [PDF] [CODE]
Complementary Knowledge Distillation for Robust and Privacy-Preserving Model Serving in Vertical Federated Learning	SUST; HKUST	AAAI	2024	[PUB] [PAGE]
Federated Learning via Input-Output Collaborative Distillation	University at Buffalo; USA Harvard Medical School	AAAI	2024	[PUB] [PAGE] [PDF] [CODE]
Calibrated One Round Federated Learning with Bayesian Inference in the Predictive Space	University of Waterloo Vector Institute	AAAI	2024	[PUB] [PAGE] [PDF] [CODE]
FedCSL: A Scalable and Accurate Approach to Federated Causal Structure Learning	HFUT	AAAI	2024	[PUB] [PDF]
FedFixer: Mitigating Heterogeneous Label Noise in Federated Learning	Xi'an Jiaotong University; Leiden University	AAAI	2024	[PUB] [PAGE] [PDF]
FedLPS: Heterogeneous Federated Learning for Multiple Tasks with Local Parameter Sharing	NJU	AAAI	2024	[PUB] [PAGE] [PDF] [CODE]
Provably Convergent Federated Trilevel Learning	TJU	AAAI	2024	[PUB] [PDF]
Performative Federated Learning: A Solution to Model-Dependent and Heterogeneous Distribution Shifts	U-M	AAAI	2024	[PUB] [PAGE]
General Commerce Intelligence: Glocally Federated NLP-Based Engine for Privacy-Preserving and Sustainable Personalized Services of Multi-Merchants	Kyung Hee University; Harex InfoTech	AAAI	2024	[PUB] [PAGE]
EMGAN: Early-Mix-GAN on Extracting Server-Side Model in Split Federated Learning	Sony AI	AAAI	2024	[PUB] [PAGE] [CODE]
FedDiv: Collaborative Noise Filtering for Federated Learning with Noisy Labels	SYSU; HKU	AAAI	2024	[PUB] [PAGE] [PDF] [CODE]
Point Transformer with Federated Learning for Predicting Breast Cancer HER2 Status from Hematoxylin and Eosin-Stained Whole Slide Images	USTC; CAS	AAAI	2024	[PUB] [PAGE] [PDF] [CODE]
FedNS: A Fast Sketching Newton-Type Algorithm for Federated Learning	CAS	AAAI	2024	[PUB] [PDF] [CODE]
Federated X-armed Bandit	Purdue University	AAAI	2024	[PUB] [PAGE] [PDF] [CODE]
Algorithmic Foundation of Federated Learning with Sequential Data	GMU	AAAI	2024	[PUB]
UFDA: Universal Federated Domain Adaptation with Practical Assumptions	XJTU; University of Sydney	AAAI	2024	[PUB] [PAGE] [PDF] [CODE]
FedASMU: Efficient Asynchronous Federated Learning with Dynamic Staleness-Aware Model Update	Hithink RoyalFlush Information Network Co	AAAI	2024	[PUB] [PAGE] [PDF]
Language-Guided Transformer for Federated Multi-Label Classification	NTU	AAAI	2024	[PUB] [PAGE] [PDF] [CODE]
FedCD: Federated Semi-Supervised Learning with Class Awareness Balance via Dual Teachers	SZU	AAAI	2024	[PUB] [PAGE] [CODE]
Beyond Traditional Threats: A Persistent Backdoor Attack on Federated Learning	HEU	AAAI	2024	[PUB] [PAGE] [CODE]
Federated Learning with Extremely Noisy Clients via Negative Distillation	XMU	AAAI	2024	[PUB] [PAGE] [PDF] [CODE]
FedST: Federated Style Transfer Learning for Non-IID Image Segmentation	USTB	AAAI	2024	[PUB] [PAGE] [学报] [CODE]
PPIDSG: A Privacy-Preserving Image Distribution Sharing Scheme with GAN in Federated Learning	USTC	AAAI	2024	[PUB] [PAGE] [PDF] [CODE]
A Privacy Preserving Federated Learning (PPFL) Based Cognitive Digital Twin (CDT) Framework for Smart Cities	DCU	AAAI	2024	[PUB]
A Primal-Dual Algorithm for Hybrid Federated Learning	Northwestern University	AAAI	2024	[PUB] [PAGE] [PDF]
FedLF: Layer-Wise Fair Federated Learning	CUHK; Shenzhen Institute of Artificial Intelligence and Robotics for Society	AAAI	2024	[PUB] [PAGE]
Towards Fair Graph Federated Learning via Incentive Mechanisms	ZJU; FDU	AAAI	2024	[PUB] [PAGE] [PDF] [CODE]
Towards the Robustness of Differentially Private Federated Learning	THU	AAAI	2024	[PUB] [PAGE]
Resisting Backdoor Attacks in Federated Learning via Bidirectional Elections and Individual Perspective	ZJU; HUAWEI	AAAI	2024	[PUB] [PAGE] [PDF] [CODE]
Integer Is Enough: When Vertical Federated Learning Meets Rounding	ZJU; Ant Group	AAAI	2024	[PUB] [PAGE]
CLIP-Guided Federated Learning on Heterogeneity and Long-Tailed Data	XMU	AAAI	2024	[PUB] [PAGE] [PDF] [CODE]
Federated Adaptive Prompt Tuning for Multi-Domain Collaborative Learning	FDU	AAAI	2024	[PUB] [PAGE] [PDF] [CODE]
Multi-Dimensional Fair Federated Learning	SDU	AAAI	2024	[PUB] [PAGE] [PDF]
HiFi-Gas: Hierarchical Federated Learning Incentive Mechanism Enhanced Gas Usage Estimation	ENN Group	AAAI	2024	[PUB]
On the Role of Server Momentum in Federated Learning	University of Virginia	AAAI	2024	[PUB] [PDF]
FedCompetitors: Harmonious Collaboration in Federated Learning with Competing Participants	BUPT	AAAI	2024	[PUB] [PAGE] [PDF]
z-SignFedAvg: A Unified Stochastic Sign-Based Compression for Federated Learning	CUHK; China Shenzhen Research Institute of Big Data	AAAI	2024	[PUB] [PAGE] [PDF]
Data Disparity and Temporal Unavailability Aware Asynchronous Federated Learning for Predictive Maintenance on Transportation Fleets	Volkswagen Group	AAAI	2024	[PUB] [PAGE]
Federated Graph Learning under Domain Shift with Generalizable Prototypes	WHU	AAAI	2024	[PUB] [PAGE]
TurboSVM-FL: Boosting Federated Learning through SVM Aggregation for Lazy Clients	Technical University of Munich	AAAI	2024	[PUB] [PAGE] [PDF] [CODE]
Multi-Source Collaborative Gradient Discrepancy Minimization for Federated Domain Generalization	TJU	AAAI	2024	[PUB] [PDF] [CODE]
Concealing Sensitive Samples against Gradient Leakage in Federated Learning	Monash University	AAAI	2024	[PUB] [PAGE] [PDF] [CODE]
FedA3I: Annotation Quality-Aware Aggregation for Federated Medical Image Segmentation against Heterogeneous Annotation Noise	HUST	AAAI	2024	[PUB] [PAGE] [PDF] [CODE]
Federated Causality Learning with Explainable Adaptive Optimization	SDU	AAAI	2024	[PUB] [PAGE] [PDF]
Federated Contextual Cascading Bandits with Asynchronous Communication and Heterogeneous Users	USTC	AAAI	2024	[PUB] [PAGE] [PDF]
Exploring One-Shot Semi-supervised Federated Learning with Pre-trained Diffusion Models	FDU	AAAI	2024	[PUB] [PDF]
Diversity-Authenticity Co-constrained Stylization for Federated Domain Generalization in Person Re-identification	XMU; University of Trento	AAAI	2024	[PUB] [PAGE]
PerFedRLNAS: One-for-All Personalized Federated Neural Architecture Search	U of T	AAAI	2024	[PUB] [PAGE]
Efficient Asynchronous Federated Learning with Prospective Momentum Aggregation and Fine-Grained Correction	BUPT	AAAI	2024	[PUB] [PAGE]
Adversarial Attacks on Federated-Learned Adaptive Bitrate Algorithms	HKU	AAAI	2024	[PUB]
FedTGP: Trainable Global Prototypes with Adaptive-Margin-Enhanced Contrastive Learning for Data and Model Heterogeneity in Federated Learning	SJTU	AAAI	2024	[PUB] [PAGE] [PDF] [CODE]
LR-XFL: Logical Reasoning-Based Explainable Federated Learning	NTU	AAAI	2024	[PUB] [PDF] [CODE]
A Huber Loss Minimization Approach to Byzantine Robust Federated Learning	Zhejiang Lab	AAAI	2024	[PUB] [PAGE] [PDF]
Knowledge-Aware Parameter Coaching for Personalized Federated Learning	Northeastern University	AAAI	2024	[PUB] [PAGE]
Federated Label-Noise Learning with Local Diversity Product Regularization	SJTU	AAAI	2024	[PUB] [PAGE] [SUPP]
Adapted Weighted Aggregation in Federated Learning (Student Abstract)	UBC	AAAI	2024	[PUB]
Knowledge Transfer via Compact Model in Federated Learning (Student Abstract)	University of Sydney	AAAI	2024	[PUB] [PAGE]
PICSR: Prototype-Informed Cross-Silo Router for Federated Learning (Student Abstract)	The Ohio State University Auton Lab, CMU	AAAI	2024	[PUB] [PAGE]
Privacy-preserving graph convolution network for federated item recommendation	SZU	AI	2023	[PUB]
Win-Win: A Privacy-Preserving Federated Framework for Dual-Target Cross-Domain Recommendation	CAS; UCAS; JD Technology; JD Intelligent Cities Research	AAAI	2023	[PUB]
Untargeted Attack against Federated Recommendation Systems via Poisonous Item Embeddings and the Defense	USTC; State Key Laboratory of Cognitive Intelligence	AAAI	2023	[PUB] [PDF] [CODE]
Incentive-Boosted Federated Crowdsourcing	SDU	AAAI	2023	[PUB] [PDF]
Tackling Data Heterogeneity in Federated Learning with Class Prototypes	Lehigh University	AAAI	2023	[PUB] [PDF] [CODE]
FairFed: Enabling Group Fairness in Federated Learning	USC	AAAI	2023	[PUB] [PDF] [解读]
Federated Robustness Propagation: Sharing Adversarial Robustness in Heterogeneous Federated Learning	MSU	AAAI	2023	[PUB]
Complement Sparsification: Low-Overhead Model Pruning for Federated Learning	NJIT	AAAI	2023	[PUB]
Almost Cost-Free Communication in Federated Best Arm Identification	NUS	AAAI	2023	[PUB] [PDF]
Layer-Wise Adaptive Model Aggregation for Scalable Federated Learning	University of Southern California Inha University	AAAI	2023	[PUB] [PDF]
Poisoning with Cerberus: Stealthy and Colluded Backdoor Attack against Federated Learning	BJTU	AAAI	2023	[PUB]
FedMDFG: Federated Learning with Multi-Gradient Descent and Fair Guidance	CUHK; The Shenzhen Institute of Artificial Intelligence and Robotics for Society	AAAI	2023	[PUB]
Securing Secure Aggregation: Mitigating Multi-Round Privacy Leakage in Federated Learning	USC	AAAI	2023	[PUB] [PDF] [VIDEO] [CODE]
Federated Learning on Non-IID Graphs via Structural Knowledge Sharing	UTS	AAAI	2023	[PUB] [PDF] [CODE]
Efficient Distribution Similarity Identification in Clustered Federated Learning via Principal Angles between Client Data Subspaces	UCSD	AAAI	2023	[PUB] [PDF] [CODE]
FedABC: Targeting Fair Competition in Personalized Federated Learning	WHU; Hubei Luojia Laboratory; JD Explore Academy	AAAI	2023	[PUB] [PDF]
Beyond ADMM: A Unified Client-Variance-Reduced Adaptive Federated Learning Framework	SUTD	AAAI	2023	[PUB] [PDF]
FedGS: Federated Graph-Based Sampling with Arbitrary Client Availability	XMU	AAAI	2023	[PUB] [PDF] [CODE]
Faster Adaptive Federated Learning	University of Pittsburgh	AAAI	2023	[PUB] [PDF]
FedNP: Towards Non-IID Federated Learning via Federated Neural Propagation	HKUST	AAAI	2023	[PUB] [CODE] [VIDEO] [SUPP]
Bayesian Federated Neural Matching That Completes Full Information	TJU	AAAI	2023	[PUB] [PDF]
CDMA: A Practical Cross-Device Federated Learning Algorithm for General Minimax Problems	ZJU	AAAI	2023	[PUB] [PDF] [CODE]
Federated Generative Model on Multi-Source Heterogeneous Data in IoT	GSU	AAAI	2023	[PUB]
DeFL: Defending against Model Poisoning Attacks in Federated Learning via Critical Learning Periods Awareness	SUNY-Binghamton University	AAAI	2023	[PUB]
FedALA: Adaptive Local Aggregation for Personalized Federated Learning	SJTU	AAAI	2023	[PUB] [PDF] [CODE]
Delving into the Adversarial Robustness of Federated Learning	ZJU	AAAI	2023	[PUB] [PDF]
On the Vulnerability of Backdoor Defenses for Federated Learning	TJU	AAAI	2023	[PUB] [PDF] [CODE]
Echo of Neighbors: Privacy Amplification for Personalized Private Federated Learning with Shuffle Model	RUC; Engineering Research Center of Ministry of Education on Database and BI	AAAI	2023	[PUB] [PDF]
DPAUC: Differentially Private AUC Computation in Federated Learning	ByteDance Inc.	AAAI Special Tracks	2023	[PUB] [PDF] [CODE]
Efficient Training of Large-Scale Industrial Fault Diagnostic Models through Federated Opportunistic Block Dropout	NTU	AAAI Special Programs	2023	[PUB] [PDF]
Industry-Scale Orchestrated Federated Learning for Drug Discovery	KU Leuven	AAAI Special Programs	2023	[PUB] [PDF] [VIDEO]
A Federated Learning Monitoring Tool for Self-Driving Car Simulation (Student Abstract)	CNU	AAAI Special Programs	2023	[PUB]
MGIA: Mutual Gradient Inversion Attack in Multi-Modal Federated Learning (Student Abstract)	PolyU	AAAI Special Programs	2023	[PUB]
Clustered Federated Learning for Heterogeneous Data (Student Abstract)	RUC	AAAI Special Programs	2023	[PUB]
FedSampling: A Better Sampling Strategy for Federated Learning	THU	IJCAI	2023	[PUB] [PDF] [CODE]
HyperFed: Hyperbolic Prototypes Exploration with Consistent Aggregation for Non-IID Data in Federated Learning	ZJU	IJCAI	2023	[PUB] [PDF]
FedOBD: Opportunistic Block Dropout for Efficiently Training Large-scale Neural Networks through Federated Learning	NTU	IJCAI	2023	[PUB] [PDF] [CODE]
Federated Probabilistic Preference Distribution Modelling with Compactness Co-Clustering for Privacy-Preserving Multi-Domain Recommendation	ZJU	IJCAI	2023	[PUB]
Federated Graph Semantic and Structural Learning	WHU	IJCAI	2023	[PUB]
BARA: Efficient Incentive Mechanism with Online Reward Budget Allocation in Cross-Silo Federated Learning	SYSU	IJCAI	2023	[PUB] [PDF]
FedDWA: Personalized Federated Learning with Dynamic Weight Adjustment	SYSU	IJCAI	2023	[PUB] [PDF]
FedPass: Privacy-Preserving Vertical Federated Deep Learning with Adaptive Obfuscation	Webank	IJCAI	2023	[PUB] [PDF]
Globally Consistent Federated Graph Autoencoder for Non-IID Graphs	FZU	IJCAI	2023	[PUB] [CODE]
Competitive-Cooperative Multi-Agent Reinforcement Learning for Auction-based Federated Learning	NTU	IJCAI	2023	[PUB]
Dual Personalization on Federated Recommendation	JLU; University of Technology Sydney	IJCAI	2023	[PUB] [PDF] [CODE]
FedNoRo: Towards Noise-Robust Federated Learning by Addressing Class Imbalance and Label Noise Heterogeneity	HUST	IJCAI	2023	[PUB] [PDF] [CODE]
Denial-of-Service or Fine-Grained Control: Towards Flexible Model Poisoning Attacks on Federated Learning	Xiangtan University	IJCAI	2023	[PUB] [PDF] [CODE]
FedHGN: A Federated Framework for Heterogeneous Graph Neural Networks	CUHK	IJCAI	2023	[PUB] [PDF] [CODE]
FedET: A Communication-Efficient Federated Class-Incremental Learning Framework Based on Enhanced Transformer	Ping An Technology; THU	IJCAI	2023	[PUB] [PDF]
Prompt Federated Learning for Weather Forecasting: Toward Foundation Models on Meteorological Data	UTS	IJCAI	2023	[PUB] [PDF] [CODE]
FedBFPT: An Efficient Federated Learning Framework for Bert Further Pre-training	ZJU	IJCAI	2023	[PUB] [CODE]
Bayesian Federated Learning: A Survey		IJCAI Survey Track	2023	[PDF]
A Survey of Federated Evaluation in Federated Learning	Macquarie University	IJCAI Survey Track	2023	[PUB] [PDF]
SAMBA: A Generic Framework for Secure Federated Multi-Armed Bandits (Extended Abstract)	INSA Centre Val de Loire	IJCAI Journal Track	2023	[PUB]
The communication cost of security and privacy in federated frequency estimation	Stanford	AISTATS	2023	[PUB] [CODE]
Efficient and Light-Weight Federated Learning via Asynchronous Distributed Dropout	Rice University	AISTATS	2023	[PUB] [CODE]
Federated Learning under Distributed Concept Drift	CMU	AISTATS	2023	[PUB] [CODE]
Characterizing Internal Evasion Attacks in Federated Learning	CMU	AISTATS	2023	[PUB] [CODE]
Federated Asymptotics: a model to compare federated learning algorithms	Stanford	AISTATS	2023	[PUB] [CODE]
Private Non-Convex Federated Learning Without a Trusted Server	USC	AISTATS	2023	[PUB] [CODE]
Federated Learning for Data Streams	Universit ́ e Cˆ ote d’Azur	AISTATS	2023	[PUB] [CODE]
Nothing but Regrets — Privacy-Preserving Federated Causal Discovery	Helmholtz Centre for Information Security	AISTATS	2023	[PUB] [CODE]
Active Membership Inference Attack under Local Differential Privacy in Federated Learning	UFL	AISTATS	2023	[PUB] [CODE]
Federated Averaging Langevin Dynamics: Toward a unified theory and new algorithms	CMAP	AISTATS	2023	[PUB]
Byzantine-Robust Federated Learning with Optimal Statistical Rates	UC Berkeley	AISTATS	2023	[PUB] [CODE]
Federated Learning on Non-IID Graphs via Structural Knowledge Sharing	UTS	AAAI	2023	[PDF] [CODE]
FedGS: Federated Graph-based Sampling with Arbitrary Client Availability	XMU	AAAI	2023	[PDF] [CODE]
Incentive-boosted Federated Crowdsourcing	SDU	AAAI	2023	[PDF]
Towards Understanding Biased Client Selection in Federated Learning.	CMU	AISTATS	2022	[PUB] [CODE]
FLIX: A Simple and Communication-Efficient Alternative to Local Methods in Federated Learning	KAUST	AISTATS	2022	[PUB] [PDF] [CODE]
Sharp Bounds for Federated Averaging (Local SGD) and Continuous Perspective.	Stanford	AISTATS	2022	[PUB] [PDF] [CODE]
Federated Reinforcement Learning with Environment Heterogeneity.	PKU	AISTATS	2022	[PUB] [PDF] [CODE]
Federated Myopic Community Detection with One-shot Communication	Purdue	AISTATS	2022	[PUB] [PDF]
Asynchronous Upper Confidence Bound Algorithms for Federated Linear Bandits.	University of Virginia	AISTATS	2022	[PUB] [PDF] [CODE]
Towards Federated Bayesian Network Structure Learning with Continuous Optimization.	CMU	AISTATS	2022	[PUB] [PDF] [CODE]
Federated Learning with Buffered Asynchronous Aggregation	Meta AI	AISTATS	2022	[PUB] [PDF] [VIDEO]
Differentially Private Federated Learning on Heterogeneous Data.	Stanford	AISTATS	2022	[PUB] [PDF] [CODE]
SparseFed: Mitigating Model Poisoning Attacks in Federated Learning with Sparsification	Princeton	AISTATS	2022	[PUB] [PDF] [CODE] [VIDEO]
Basis Matters: Better Communication-Efficient Second Order Methods for Federated Learning	KAUST	AISTATS	2022	[PUB] [PDF]
Federated Functional Gradient Boosting.	University of Pennsylvania	AISTATS	2022	[PUB] [PDF] [CODE]
QLSD: Quantised Langevin Stochastic Dynamics for Bayesian Federated Learning.	Criteo AI Lab	AISTATS	2022	[PUB] [PDF] [CODE] [VIDEO]
Meta-Learning Based Knowledge Extrapolation for Knowledge Graphs in the Federated Setting `kg.`	ZJU	IJCAI	2022	[PUB] [PDF] [CODE]
Personalized Federated Learning With a Graph	UTS	IJCAI	2022	[PUB] [PDF] [CODE]
Vertically Federated Graph Neural Network for Privacy-Preserving Node Classification	ZJU	IJCAI	2022	[PUB] [PDF]
Adapt to Adaptation: Learning Personalization for Cross-Silo Federated Learning		IJCAI	2022	[PUB] [PDF] [CODE]
Heterogeneous Ensemble Knowledge Transfer for Training Large Models in Federated Learning		IJCAI	2022	[PUB] [PDF]
Private Semi-Supervised Federated Learning.		IJCAI	2022	[PUB]
Continual Federated Learning Based on Knowledge Distillation.		IJCAI	2022	[PUB]
Federated Learning on Heterogeneous and Long-Tailed Data via Classifier Re-Training with Federated Features		IJCAI	2022	[PUB] [PDF] [CODE]
Federated Multi-Task Attention for Cross-Individual Human Activity Recognition		IJCAI	2022	[PUB]
Personalized Federated Learning with Contextualized Generalization.		IJCAI	2022	[PUB] [PDF]
Shielding Federated Learning: Robust Aggregation with Adaptive Client Selection.		IJCAI	2022	[PUB] [PDF]
FedCG: Leverage Conditional GAN for Protecting Privacy and Maintaining Competitive Performance in Federated Learning		IJCAI	2022	[PUB] [PDF] [CODE]
FedDUAP: Federated Learning with Dynamic Update and Adaptive Pruning Using Shared Data on the Server.		IJCAI	2022	[PUB] [PDF]
Towards Verifiable Federated Learning `surv.`		IJCAI	2022	[PUB] [PDF]
HarmoFL: Harmonizing Local and Global Drifts in Federated Learning on Heterogeneous Medical Images	CUHK; BUAA	AAAI	2022	[PUB] [PDF] [CODE] [解读]
Federated Learning for Face Recognition with Gradient Correction	BUPT	AAAI	2022	[PUB] [PDF]
SpreadGNN: Decentralized Multi-Task Federated Learning for Graph Neural Networks on Molecular Data	USC	AAAI	2022	[PUB] [PDF] [CODE] [解读]
SmartIdx: Reducing Communication Cost in Federated Learning by Exploiting the CNNs Structures	HIT; PCL	AAAI	2022	[PUB] [CODE]
Bridging between Cognitive Processing Signals and Linguistic Features via a Unified Attentional Network	TJU	AAAI	2022	[PUB] [PDF]
Seizing Critical Learning Periods in Federated Learning	SUNY-Binghamton University	AAAI	2022	[PUB] [PDF]
Coordinating Momenta for Cross-silo Federated Learning	University of Pittsburgh	AAAI	2022	[PUB] [PDF]
FedProto: Federated Prototype Learning over Heterogeneous Devices	UTS	AAAI	2022	[PUB] [PDF] [CODE]
FedSoft: Soft Clustered Federated Learning with Proximal Local Updating	CMU	AAAI	2022	[PUB] [PDF] [CODE]
Federated Dynamic Sparse Training: Computing Less, Communicating Less, Yet Learning Better	The University of Texas at Austin	AAAI	2022	[PUB] [PDF] [CODE]
FedFR: Joint Optimization Federated Framework for Generic and Personalized Face Recognition	National Taiwan University	AAAI	2022	[PUB] [PDF] [CODE]
SplitFed: When Federated Learning Meets Split Learning	CSIRO	AAAI	2022	[PUB] [PDF] [CODE]
Efficient Device Scheduling with Multi-Job Federated Learning	Soochow University	AAAI	2022	[PUB] [PDF]
Implicit Gradient Alignment in Distributed and Federated Learning	IIT Kanpur	AAAI	2022	[PUB] [PDF]
Federated Nearest Neighbor Classification with a Colony of Fruit-Flies	IBM Research	AAAI	2022	[PUB] [PDF] [CODE]
Iterated Vector Fields and Conservatism, with Applications to Federated Learning.	Google	ALT	2022	[PUB] [PDF]
Federated Learning with Sparsification-Amplified Privacy and Adaptive Optimization		IJCAI	2021	[PUB] [PDF] [VIDEO]
Behavior Mimics Distribution: Combining Individual and Group Behaviors for Federated Learning		IJCAI	2021	[PUB] [PDF]
FedSpeech: Federated Text-to-Speech with Continual Learning		IJCAI	2021	[PUB] [PDF]
Practical One-Shot Federated Learning for Cross-Silo Setting		IJCAI	2021	[PUB] [PDF] [CODE]
Federated Model Distillation with Noise-Free Differential Privacy		IJCAI	2021	[PUB] [PDF] [VIDEO]
LDP-FL: Practical Private Aggregation in Federated Learning with Local Differential Privacy		IJCAI	2021	[PUB] [PDF]
Federated Learning with Fair Averaging.		IJCAI	2021	[PUB] [PDF] [CODE]
H-FL: A Hierarchical Communication-Efficient and Privacy-Protected Architecture for Federated Learning.		IJCAI	2021	[PUB] [PDF]
Communication-efficient and Scalable Decentralized Federated Edge Learning.		IJCAI	2021	[PUB]
Secure Bilevel Asynchronous Vertical Federated Learning with Backward Updating	Xidian University; JD Tech	AAAI	2021	[PUB] [PDF] [VIDEO]
FedRec++: Lossless Federated Recommendation with Explicit Feedback	SZU	AAAI	2021	[PUB] [VIDEO]
Federated Multi-Armed Bandits	University of Virginia	AAAI	2021	[PUB] [PDF] [CODE] [VIDEO]
On the Convergence of Communication-Efficient Local SGD for Federated Learning	Temple University; University of Pittsburgh	AAAI	2021	[PUB] [VIDEO]
FLAME: Differentially Private Federated Learning in the Shuffle Model	Renmin University of China; Kyoto University	AAAI	2021	[PUB] [PDF] [VIDEO] [CODE]
Toward Understanding the Influence of Individual Clients in Federated Learning	SJTU; The University of Texas at Dallas	AAAI	2021	[PUB] [PDF] [VIDEO]
Provably Secure Federated Learning against Malicious Clients	Duke University	AAAI	2021	[PUB] [PDF] [VIDEO] [SLIDE]
Personalized Cross-Silo Federated Learning on Non-IID Data	Simon Fraser University; McMaster University	AAAI	2021	[PUB] [PDF] [VIDEO] [UC.]
Model-Sharing Games: Analyzing Federated Learning under Voluntary Participation	Cornell University	AAAI	2021	[PUB] [PDF] [CODE] [VIDEO]
Curse or Redemption? How Data Heterogeneity Affects the Robustness of Federated Learning	University of Nevada; IBM Research	AAAI	2021	[PUB] [PDF] [VIDEO]
Game of Gradients: Mitigating Irrelevant Clients in Federated Learning	IIT Bombay; IBM Research	AAAI	2021	[PUB] [PDF] [CODE] [VIDEO] [SUPP]
Federated Block Coordinate Descent Scheme for Learning Global and Personalized Models	CUHK; Arizona State University	AAAI	2021	[PUB] [PDF] [VIDEO] [CODE]
Addressing Class Imbalance in Federated Learning	Northwestern University	AAAI	2021	[PUB] [PDF] [VIDEO] [CODE] [解读]
Defending against Backdoors in Federated Learning with Robust Learning Rate	The University of Texas at Dallas	AAAI	2021	[PUB] [PDF] [VIDEO] [CODE]
Free-rider Attacks on Model Aggregation in Federated Learning	Accenture Labs	AISTATS	2021	[PUB] [PDF] [CODE] [VIDEO] [SUPP]
Federated f-differential privacy	University of Pennsylvania	AISTATS	2021	[PUB] [CODE] [VIDEO] [SUPP]
Federated learning with compression: Unified analysis and sharp guarantees	The Pennsylvania State University; The University of Texas at Austin	AISTATS	2021	[PUB] [PDF] [CODE] [VIDEO] [SUPP]
Shuffled Model of Differential Privacy in Federated Learning	UCLA; Google	AISTATS	2021	[PUB] [VIDEO] [SUPP]
Convergence and Accuracy Trade-Offs in Federated Learning and Meta-Learning	Google	AISTATS	2021	[PUB] [PDF] [VIDEO] [SUPP]
Federated Multi-armed Bandits with Personalization	University of Virginia; The Pennsylvania State University	AISTATS	2021	[PUB] [PDF] [CODE] [VIDEO] [SUPP]
Towards Flexible Device Participation in Federated Learning	CMU; SYSU	AISTATS	2021	[PUB] [PDF] [VIDEO] [SUPP]
Federated Meta-Learning for Fraudulent Credit Card Detection		IJCAI	2020	[PUB] [VIDEO]
A Multi-player Game for Studying Federated Learning Incentive Schemes		IJCAI	2020	[PUB] [CODE] [解读]
Practical Federated Gradient Boosting Decision Trees	NUS; UWA	AAAI	2020	[PUB] [PDF] [CODE]
Federated Learning for Vision-and-Language Grounding Problems	PKU; Tencent	AAAI	2020	[PUB]
Federated Latent Dirichlet Allocation: A Local Differential Privacy Based Framework	BUAA	AAAI	2020	[PUB]
Federated Patient Hashing	Cornell University	AAAI	2020	[PUB]
Robust Federated Learning via Collaborative Machine Teaching	Symantec Research Labs; KAUST	AAAI	2020	[PUB] [PDF]
FedVision: An Online Visual Object Detection Platform Powered by Federated Learning	WeBank	AAAI	2020	[PUB] [PDF] [CODE]
FedPAQ: A Communication-Efficient Federated Learning Method with Periodic Averaging and Quantization	UC Santa Barbara; UT Austin	AISTATS	2020	[PUB] [PDF] [VIDEO] [SUPP]
How To Backdoor Federated Learning	Cornell Tech	AISTATS	2020	[PUB] [PDF] [VIDEO] [CODE] [SUPP]
Federated Heavy Hitters Discovery with Differential Privacy	RPI; Google	AISTATS	2020	[PUB] [PDF] [VIDEO] [SUPP]
Multi-Agent Visualization for Explaining Federated Learning	WeBank	IJCAI	2019	[PUB] [VIDEO]

fl in top ml conference and journal

Federated Learning papers accepted by top ML(machine learning) conference and journal, Including NeurIPS(Annual Conference on Neural Information Processing Systems), ICML(International Conference on Machine Learning), ICLR(International Conference on Learning Representations), COLT(Annual Conference Computational Learning Theory) , UAI(Conference on Uncertainty in Artificial Intelligence),Machine Learning, JMLR(Journal of Machine Learning Research), TPAMI(IEEE Transactions on Pattern Analysis and Machine Intelligence).

NeurIPS 2023(OpenReview), 2022(OpenReview), 2021(OpenReview), 2020, 2018, 2017
ICML 2023, 2022, 2021, 2020, 2019
ICLR 2024, 2023, 2022, 2021, 2020
COLT 2023
UAI 2023, 2022, 2021
Machine Learning 2024, 2023, 2022
JMLR 2023(v24), 2021(v22)
TPAMI 2023, 2022

fl in top ml conference and journal

Title	Affiliation	Venue	Year	Materials
Aligning model outputs for class imbalanced non-IID federated learning	NJU	Mach Learn	2024	[PUB]
The Impact of Adversarial Attacks on Federated Learning: A Survey	IIT	TPAMI	2024	[PUB]
Understanding and Mitigating Dimensional Collapse in Federated Learning	NUS	TPAMI	2024	[PUB] [PDF] [CODE]
No One Left Behind: Real-World Federated Class-Incremental Learning	CAS; UCAS	TPAMI	2024	[PUB] [PDF] [CODE]
Generalizable Heterogeneous Federated Cross-Correlation and Instance Similarity Learning	WHU	TPAMI	2024	[PUB] [PDF] [CODE]
Multi-Stage Asynchronous Federated Learning With Adaptive Differential Privacy	HPU; XJTU	TPAMI	2024	[PUB] [PDF] [CODE]
A Bayesian Federated Learning Framework With Online Laplace Approximation	SUSTech	TPAMI	2024	[PUB] [PDF] [CODE]
One-shot Empirical Privacy Estimation for Federated Learning	Google	ICLR	2024	[PUB] [PDF]
Stochastic Controlled Averaging for Federated Learning with Communication Compression	LinkedIn; UPenn	ICLR	2024	[PUB] [PDF]
A Lightweight Method for Tackling Unknown Participation Statistics in Federated Averaging	IBM	ICLR	2024	[PUB] [PDF] [CODE]
A Mutual Information Perspective on Federated Contrastive Learning	QualComm	ICLR	2024	[PUB]
Benchmarking Algorithms for Federated Domain Generalization	Purdue University	ICLR	2024	[PUB] [PDF] [CODE]
Effective and Efficient Federated Tree Learning on Hybrid Data	UC Berkeley	ICLR	2024	[PUB] [PDF]
Federated Recommendation with Additive Personalization	UTS	ICLR	2024	[PUB] [PDF] [CODE]
Tackling the Data Heterogeneity in Asynchronous Federated Learning with Cached Update Calibration	PSU	ICLR	2024	[PUB] [SUPP]
Federated Orthogonal Training: Mitigating Global Catastrophic Forgetting in Continual Federated Learning	USC	ICLR	2024	[PUB] [SUPP] [PDF]
Accurate Forgetting for Heterogeneous Federated Continual Learning	THU	ICLR	2024	[PUB] [CODE]
Federated Causal Discovery from Heterogeneous Data	MBZUAI	ICLR	2024	[PUB] [PDF] [CODE]
On Differentially Private Federated Linear Contextual Bandits	Wayne State University	ICLR	2024	[PUB] [SUPP] [PDF]
Incentivized Truthful Communication for Federated Bandits	University of Virginia	ICLR	2024	[PUB] [PDF]
Principled Federated Domain Adaptation: Gradient Projection and Auto-Weighting	UIUC	ICLR	2024	[PUB]
FedP3: Federated Personalized and Privacy-friendly Network Pruning under Model Heterogeneity	KAUST	ICLR	2024	[PUB]
Text-driven Prompt Generation for Vision-Language Models in Federated Learning	Robert Bosch LLC	ICLR	2024	[PUB] [PDF]
Improving LoRA in Privacy-preserving Federated Learning	Northeastern University	ICLR	2024	[PUB]
FedWon: Triumphing Multi-domain Federated Learning Without Normalization	Sony AI	ICLR	2024	[PUB] [PDF]
FedTrans: Client-Transparent Utility Estimation for Robust Federated Learning	TU Delft	ICLR	2024	[PUB]
FedCompass: Efficient Cross-Silo Federated Learning on Heterogeneous Client Devices Using a Computing Power-Aware Scheduler	ANL; UIUC; NCSA	ICLR	2024	[PUB] [PDF] [CODE] [PAGE]
Bayesian Coreset Optimization for Personalized Federated Learning	IIT Bombay	ICLR	2024	[PUB]
Layer-wise linear mode connectivity	Ruhr-Universtät Bochum	ICLR	2024	[PUB] [PDF] [SUPP]
Fake It Till Make It: Federated Learning with Consensus-Oriented Generation	SJTU	ICLR	2024	[PUB] [PDF]
Hiding in Plain Sight: Disguising Data Stealing Attacks in Federated Learning	INSAIT	ICLR	2024	[PUB] [SUPP] [PDF]
Finite-Time Analysis of On-Policy Heterogeneous Federated Reinforcement Learning	Columbia University	ICLR	2024	[PUB] [PDF]
Adaptive Federated Learning with Auto-Tuned Clients	Rice University	ICLR	2024	[PUB] [SUPP] [PDF]
Backdoor Federated Learning by Poisoning Backdoor-Critical Layers	ND	ICLR	2024	[PUB] [SUPP] [PDF]
Federated Q-Learning: Linear Regret Speedup with Low Communication Cost	PSU	ICLR	2024	[PUB] [SUPP] [PDF]
FedImpro: Measuring and Improving Client Update in Federated Learning	HKBU	ICLR	2024	[PUB] [PDF]
Federated Wasserstein Distance	MIT	ICLR	2024	[PUB] [SUPP] [PDF]
An improved analysis of per-sample and per-update clipping in federated learning	DTU	ICLR	2024	[PUB]
FedCDA: Federated Learning with Cross-rounds Divergence-aware Aggregation	NTU	ICLR	2024	[PUB] [SUPP]
Internal Cross-layer Gradients for Extending Homogeneity to Heterogeneity in Federated Learning	HKU	ICLR	2024	[PUB] [PDF]
Momentum Benefits Non-iid Federated Learning Simply and Provably	PKU; UPenn	ICLR	2024	[PUB] [PDF]
Communication-Efficient Federated Non-Linear Bandit Optimization	Yale University	ICLR	2024	[PUB] [PDF]
Fair and Efficient Contribution Valuation for Vertical Federated Learning	Huawei	ICLR	2024	[PUB] [SUPP] [PDF] [CODE]
Demystifying Local & Global Fairness Trade-offs in Federated Learning Using Partial Information Decomposition	UMCP	ICLR	2024	[PUB] [PDF]
Learning Personalized Causally Invariant Representations for Heterogeneous Federated Clients	PolyU	ICLR	2024	[PUB]
PeFLL: Personalized Federated Learning by Learning to Learn	IST	ICLR	2024	[PUB] [SUPP] [PDF]
Communication-Efficient Gradient Descent-Accent Methods for Distributed Variational Inequalities: Unified Analysis and Local Updates	JHU	ICLR	2024	[PUB] [SUPP] [PDF]
FedInverse: Evaluating Privacy Leakage in Federated Learning	USQ	ICLR	2024	[PUB] [SUPP]
FedDA: Faster Adaptive Gradient Methods for Federated Constrained Optimization	UMCP	ICLR	2024	[PUB] [SUPP] [PDF]
Robust Training of Federated Models with Extremely Label Deficiency	HKBU	ICLR	2024	[PUB] [PDF] [CODE]
Understanding Convergence and Generalization in Federated Learning through Feature Learning Theory	RIKEN AIP	ICLR	2024	[PUB]
Teach LLMs to Phish: Stealing Private Information from Language Models	Princeton University	ICLR	2024	[PUB]
Like Oil and Water: Group Robustness Methods and Poisoning Defenses Don't Mix	UMCP	ICLR	2024	[PUB]
Accelerated Convergence of Stochastic Heavy Ball Method under Anisotropic Gradient Noise	HKUST	ICLR	2024	[PUB] [PDF]
Towards Eliminating Hard Label Constraints in Gradient Inversion Attacks	CAS	ICLR	2024	[PUB] [SUPP] [PDF] [CODE]
Local Composite Saddle Point Optimization	Purdue University	ICLR	2024	[PUB] [PDF]
Enhancing Neural Training via a Correlated Dynamics Model	TIIT	ICLR	2024	[PUB] [PDF]
EControl: Fast Distributed Optimization with Compression and Error Control	Saarland University	ICLR	2024	[PUB] [SUPP] [PDF]
Constructing Adversarial Examples for Vertical Federated Learning: Optimal Client Corruption through Multi-Armed Bandit	HKUST	ICLR	2024	[PUB]
FedHyper: A Universal and Robust Learning Rate Scheduler for Federated Learning with Hypergradient Descent	UMCP	ICLR	2024	[PUB] [SUPP] [PDF] [CODE]
Heterogeneous Personalized Federated Learning by Local-Global Updates Mixing via Convergence Rate	CUHK	ICLR	2024	[PUB]
Breaking Physical and Linguistic Borders: Multilingual Federated Prompt Tuning for Low-Resource Languages	University of Cambridge	ICLR	2024	[PUB]
Simple Minimax Optimal Byzantine Robust Algorithm for Nonconvex Objectives with Uniform Gradient Heterogeneity	NTT DATA Mathematical Systems Inc.	ICLR	2024	[PUB]
VFLAIR: A Research Library and Benchmark for Vertical Federated Learning	THU	ICLR	2024	[PUB] [PDF] [CODE]
Incentive-Aware Federated Learning with Training-Time Model Rewards	NUS	ICLR	2024	[PUB] [SUPP]
VertiBench: Advancing Feature Distribution Diversity in Vertical Federated Learning Benchmarks	NUS	ICLR	2024	[PUB] [PDF] [CODE]
FedLoGe: Joint Local and Generic Federated Learning under Long-tailed Data	ZJU	ICLR	2024	[PUB] [SUPP] [PDF]
SimFBO: Towards Simple, Flexible and Communication-efficient Federated Bilevel Learning	University at Buffalo	NeurIPS	2023	[PUB] [PDF] [SUPP]
Mechanism Design for Collaborative Normal Mean Estimation	UW-Madison	NeurIPS	2023	[PUB] [PDF]
Robust Distributed Learning: Tight Error Bounds and Breakdown Point under Data Heterogeneity	EPFL	NeurIPS	2023	[PUB] [PDF] [CODE]
Incentives in Federated Learning: Equilibria, Dynamics, and Mechanisms for Welfare Maximization	UIUC	NeurIPS	2023	[PUB] [SUPP]
Convergence Analysis of Sequential Federated Learning on Heterogeneous Data	BUPT	NeurIPS	2023	[PUB] [PDF] [CODE]
Handling Data Heterogeneity via Architectural Design for Federated Visual Recognition	MBZUAI	NeurIPS	2023	[PUB] [PDF] [CODE]
Private Federated Frequency Estimation: Adapting to the Hardness of the Instance	JHU	NeurIPS	2023	[PUB] [SUPP] [PDF]
Zeroth-Order Methods for Nondifferentiable, Nonconvex, and Hierarchical Federated Optimization	Rutgers University	NeurIPS	2023	[PUB] [SUPP] [PDF]
Incentivized Communication for Federated Bandits	University of Virginia	NeurIPS	2023	[PUB] [PDF]
Multiply Robust Federated Estimation of Targeted Average Treatment Effects	Northeastern University	NeurIPS	2023	[PUB] [PDF]
IBA: Towards Irreversible Backdoor Attacks in Federated Learning	Vanderbilt University; VinUniversity	NeurIPS	2023	[PUB] [SUPP] [CODE]
EvoFed: Leveraging Evolutionary Strategies for Communication-Efficient Federated Learning	KAIST	NeurIPS	2023	[PUB] [SUPP] [PDF]
Federated Linear Bandits with Finite Adversarial Actions	University of Virginia	NeurIPS	2023	[PUB] [SUPP] [PDF]
FedNAR: Federated Optimization with Normalized Annealing Regularization	MBZUAI	NeurIPS	2023	[PUB] [SUPP] [PDF] [CODE]
Guiding The Last Layer in Federated Learning with Pre-Trained Models	Concordia University	NeurIPS	2023	[PUB] [SUPP] [PDF] [CODE]
Fine-Grained Theoretical Analysis of Federated Zeroth-Order Optimization	HZAU	NeurIPS	2023	[PUB] [SUPP]
Navigating Data Heterogeneity in Federated Learning: A Semi-Supervised Approach for Object Detection	KAIST	NeurIPS	2023	[PUB] [SUPP] [PDF] [CODE]
A Data-Free Approach to Mitigate Catastrophic Forgetting in Federated Class Incremental Learning for Vision Tasks	USC	NeurIPS	2023	[PUB] [PDF] [CODE]
Is Heterogeneity Notorious? Taming Heterogeneity to Handle Test-Time Shift in Federated Learning	UTS	NeurIPS	2023	[PUB] [SUPP]
One-Pass Distribution Sketch for Measuring Data Heterogeneity in Federated Learning	Rice University	NeurIPS	2023	[PUB] [SUPP] [CODE]
Lockdown: Backdoor Defense for Federated Learning with Isolated Subspace Training	Gatech	NeurIPS	2023	[PUB] [SUPP] [CODE]
FedGame: A Game-Theoretic Defense against Backdoor Attacks in Federated Learning	PSU; UIUC	NeurIPS	2023	[PUB] [SUPP] [CODE]
Towards Personalized Federated Learning via Heterogeneous Model Reassembly	PSU	NeurIPS	2023	[PUB] [SUPP] [PDF] [CODE]
Every Parameter Matters: Ensuring the Convergence of Federated Learning with Dynamic Heterogeneous Models Reduction	GWU	NeurIPS	2023	[PUB] [SUPP] [PDF]
DFRD: Data-Free Robustness Distillation for Heterogeneous Federated Learning	ECNU	NeurIPS	2023	[PUB] [SUPP] [PDF] [CODE]
A Unified Solution for Privacy and Communication Efficiency in Vertical Federated Learning	Western University	NeurIPS	2023	[PUB] [SUPP] [CODE]
RECESS Vaccine for Federated Learning: Proactive Defense Against Model Poisoning Attacks	Xidian University; University of Guelph; Zhejiang Key Laboratory of Multi-dimensional Perception Technology, Application and Cybersecurity	NeurIPS	2023	[PUB] [SUPP] [PDF]
Federated Learning with Bilateral Curation for Partially Class-Disjoint Data	SJTU; Shanghai AI Laboratory	NeurIPS	2023	[PUB] [SUPP] [CODE]
Federated Learning with Client Subsampling, Data Heterogeneity, and Unbounded Smoothness: A New Algorithm and Lower Bounds	GMU; SJTU	NeurIPS	2023	[PUB] [SUPP] [CODE]
FedL2P: Federated Learning to Personalize	University of Cambridge; Samsung AI Center	NeurIPS	2023	[PUB] [SUPP] [PDF] [CODE]
Adaptive Test-Time Personalization for Federated Learning	UIUC	NeurIPS	2023	[PUB] [PDF] [CODE]
Federated Conditional Stochastic Optimization	University of Pittsburgh	NeurIPS	2023	[PUB] [SUPP] [PDF] [CODE]
Federated Spectral Clustering via Secure Similarity Reconstruction	CUHK	NeurIPS	2023	[PUB]
Mobilizing Personalized Federated Learning in Infrastructure-Less and Heterogeneous Environments via Random Walk Stochastic ADMM	UM-Dearborn	NeurIPS	2023	[PUB] [SUPP] [PDF]
FedGCN: Convergence-Communication Tradeoffs in Federated Training of Graph Convolutional Networks	CMU	NeurIPS	2023	[PUB] [SUPP] [PDF] [CODE]
Federated Multi-Objective Learning	RIT	NeurIPS	2023	[PUB] [SUPP] [PDF]
FLuID: Mitigating Stragglers in Federated Learning using Invariant Dropout	University of British Columbia; Gatech	NeurIPS	2023	[PUB] [SUPP] [PDF] [CODE]
Resolving the Tug-of-War: A Separation of Communication and Learning in Federated Learning	University of Pittsburgh	NeurIPS	2023	[PUB] [SUPP]
Communication-Efficient Federated Bilevel Optimization with Global and Local Lower Level Problems	University of Pittsburgh	NeurIPS	2023	[PUB] [SUPP] [PDF]
StableFDG: Style and Attention Based Learning for Federated Domain Generalization	KAIST; Purdue University	NeurIPS	2023	[PUB] [PDF]
Understanding How Consistency Works in Federated Learning via Stage-wise Relaxed Initialization	The University of Sydney	NeurIPS	2023	[PUB] [SUPP] [PDF]
DELTA: Diverse Client Sampling for Fasting Federated Learning	CUHK; The Shenzhen Institute of Artificial Intelligence and Robotics for Society	NeurIPS	2023	[PUB] [SUPP] [PDF]
Federated Compositional Deep AUC Maximization	Temple University	NeurIPS	2023	[PUB] [SUPP] [PDF]
A3FL: Adversarially Adaptive Backdoor Attacks to Federated Learning	PSU	NeurIPS	2023	[PUB] [SUPP] [CODE]
Flow: Per-instance Personalized Federated Learning	University of Massachusetts	NeurIPS	2023	[PUB] [SUPP] [PDF] [CODE]
Eliminating Domain Bias for Federated Learning in Representation Space	SJTU	NeurIPS	2023	[PUB] [SUPP] [PDF] [CODE]
Federated Learning with Manifold Regularization and Normalized Update Reaggregation	BIT	NeurIPS	2023	[PUB] [SUPP] [PDF]
Structured Federated Learning through Clustered Additive Modeling	University of Technology Sydney	NeurIPS	2023	[PUB] [SUPP]
Fed-GraB: Federated Long-tailed Learning with Self-Adjusting Gradient Balancer	ZJU; Singapore University of Technology and Design	NeurIPS	2023	[PUB] [SUPP] [PDF] [CODE]
Dynamic Personalized Federated Learning with Adaptive Differential Privacy	WHU	NeurIPS	2023	[PUB] [SUPP] [CODE]
Fed-CO$_{2}$ : Cooperation of Online and Offline Models for Severe Data Heterogeneity in Federated Learning	ShanghaiTech University	NeurIPS	2023	[PUB] [SUPP] [PDF] [CODE]
Solving a Class of Non-Convex Minimax Optimization in Federated Learning	University of Pittsburgh	NeurIPS	2023	[PUB] [SUPP] [PDF] [CODE]
Federated Learning via Meta-Variational Dropout	SNU	NeurIPS	2023	[PUB] [CODE]
Improved Communication Efficiency in Federated Natural Policy Gradient via ADMM-based Gradient Updates	Purdue University	NeurIPS	2023	[PUB] [SUPP] [PDF]
SPACE: Single-round Participant Amalgamation for Contribution Evaluation in Federated Learning	NTU	NeurIPS	2023	[PUB] [CODE]
Fed-FA: Theoretically Modeling Client Data Divergence for Federated Language Backdoor Defense	PKU; Tencent	NeurIPS	2023	[PUB] [SUPP]
FedFed: Feature Distillation against Data Heterogeneity in Federated Learning	BUAA; HKBU	NeurIPS	2023	[PUB] [PDF] [CODE]
PRIOR: Personalized Prior for Reactivating the Information Overlooked in Federated Learning	SCU	NeurIPS	2023	[PUB] [SUPP] [PDF] [CODE] [解读]
Spectral Co-Distillation for Personalized Federated Learning	SUTD	NeurIPS	2023	[PUB]
Breaking the Communication-Privacy-Accuracy Tradeoff with $f$-Differential Privacy	ZJU	NeurIPS	2023	[PUB] [SUPP] [PDF]
Exact Optimality of Communication-Privacy-Utility Tradeoffs in Distributed Mean Estimation	Stanford University	NeurIPS	2023	[PUB] [SUPP] [PDF] [CODE]
(Amplified) Banded Matrix Factorization: A unified approach to private training	Google DeepMind	NeurIPS	2023	[PUB] [SUPP] [PDF]
Aggregating Capacity in FL through Successive Layer Training for Computationally-Constrained Devices	KIT	NeurIPS	2023	[PUB] [SUPP] [PDF] [CODE]
Privacy Amplification via Compression: Achieving the Optimal Privacy-Accuracy-Communication Trade-off in Distributed Mean Estimation	Stanford University	NeurIPS	2023	[PUB] [SUPP] [PDF]
Incentivizing Honesty among Competitors in Collaborative Learning and Optimization	ETH Zurich	NeurIPS	2023	[PUB] [SUPP] [PDF]
Resilient Constrained Learning	UPenn	NeurIPS	2023	[PUB] [SUPP] [PDF]
A Computation and Communication Efficient Method for Distributed Nonconvex Problems in the Partial Participation Setting	KAUST	NeurIPS	2023	[PUB] [SUPP] [PDF] [CODE]
Collaboratively Learning Linear Models with Structured Missing Data	Stanford University	NeurIPS	2023	[PUB] [SUPP] [PDF] [CODE]
Gradient Descent with Linearly Correlated Noise: Theory and Applications to Differential Privacy	EPFL	NeurIPS	2023	[PUB] [SUPP] [PDF]
Fast Optimal Locally Private Mean Estimation via Random Projections	Apple Inc.	NeurIPS	2023	[PUB] [SUPP] [PDF] [CODE]
Contextual Stochastic Bilevel Optimization	EPFL; ETH Zürich	NeurIPS	2023	[PUB] [SUPP] [PDF]
Understanding Deep Gradient Leakage via Inversion Influence Functions	MSU; Michigan State University; University of Texas at Austin	NeurIPS	2023	[PUB] [SUPP] [PDF] [CODE]
Inner Product-based Neural Network Similarity	Purdue University	NeurIPS	2023	[PUB] [SUPP]
Correlation Aware Sparsified Mean Estimation Using Random Projection	CMU	NeurIPS	2023	[PUB] [SUPP] [PDF] [CODE]
TIES-Merging: Resolving Interference When Merging Models	UNC	NeurIPS	2023	[PUB] [SUPP] [PDF] [CODE]
Global Update Tracking: A Decentralized Learning Algorithm for Heterogeneous Data	Purdue University	NeurIPS	2023	[PUB] [SUPP] [PDF] [CODE]
Large-Scale Distributed Learning via Private On-Device LSH	UMD	NeurIPS	2023	[PUB] [SUPP] [PDF]
Faster Relative Entropy Coding with Greedy Rejection Coding	University of Cambridge	NeurIPS	2023	[PUB] [SUPP] [PDF] [CODE]
Global Convergence Analysis of Local SGD for Two-layer Neural Network without Overparameterization	SJTU	NeurIPS	2023	[PUB] [SUPP]
Momentum Provably Improves Error Feedback!	ETH AI Center; ETH Zurich	NeurIPS	2023	[PUB] [SUPP] [PDF]
Strategic Data Sharing between Competitors	Sofia University	NeurIPS	2023	[PUB] [SUPP] [PDF]
H-nobs: Achieving Certified Fairness and Robustness in Distributed Learning on Heterogeneous Datasets	GMU	NeurIPS	2023	[PUB]
Wyze Rule: Federated Rule Dataset for Rule Recommendation Benchmarking	Wyze Labs	NeurIPS Datasets and Benchmarks	2023	[PUB] [SUPP] [DATASET]
Towards Federated Foundation Models: Scalable Dataset Pipelines for Group-Structured Learning	Google Research	NeurIPS Datasets and Benchmarks	2023	[PUB] [PDF] [DATASET]
Text-driven Prompt Generation for Vision-Language Models in Federated Learning		NeurIPS workshop	2023	[PUB]
HePCo: Data-Free Heterogeneous Prompt Consolidation for Continual Federated Learning		NeurIPS workshop	2023	[PUB]
Beyond Gradient and Priors in Privacy Attacks: Leveraging Pooler Layer Inputs of Language Models in Federated Learning		NeurIPS workshop	2023	[PUB]
FOCUS: Fairness via Agent-Awareness for Federated Learning on Heterogeneous Data		NeurIPS workshop	2023	[PUB]
FedSoL: Bridging Global Alignment and Local Generality in Federated Learning		NeurIPS workshop	2023	[PUB]
One-shot Empirical Privacy Estimation for Federated Learning		NeurIPS workshop	2023	[PUB]
Profit: Benchmarking Personalization and Robustness Trade-off in Federated Prompt Tuning		NeurIPS workshop	2023	[PUB]
SLoRA: Federated Parameter Efficient Fine-Tuning of Language Models		NeurIPS workshop	2023	[PUB]
The Fair Value of Data Under Heterogeneous Privacy Constraints in Federated Learning		NeurIPS workshop	2023	[PUB]
Towards Building the FederatedGPT: Federated Instruction Tuning		NeurIPS workshop	2023	[PUB]
Federated Learning for Speech Recognition: Revisiting Current Trends Towards Large-Scale ASR		NeurIPS workshop	2023	[PUB]
LASER: Linear Compression in Wireless Distributed Optimization		NeurIPS workshop	2023	[PUB]
MARINA Meets Matrix Stepsizes: Variance Reduced Distributed Non-Convex Optimization		NeurIPS workshop	2023	[PUB]
TAMUNA: Doubly Accelerated Federated Learning with Local Training, Compression, and Partial Participation		NeurIPS workshop	2023	[PUB]
An Empirical Evaluation of Federated Contextual Bandit Algorithms		NeurIPS workshop	2023	[PUB]
RealFM: A Realistic Mechanism to Incentivize Data Contribution and Device Participation		NeurIPS workshop	2023	[PUB]
FDAPT: Federated Domain-adaptive Pre-training for Language Models		NeurIPS workshop	2023	[PUB]
Making Batch Normalization Great in Federated Deep Learning		NeurIPS workshop	2023	[PUB]
Correlated Noise Provably Beats Independent Noise for Differentially Private Learning		NeurIPS workshop	2023	[PUB]
Parameter Averaging Laws for Multitask Language Models		NeurIPS workshop	2023	[PUB]
Breaking Physical and Linguistic Borders: Multilingual Federated Prompt Tuning for Low-Resource Languages		NeurIPS workshop	2023	[PUB]
Beyond Parameter Averaging in Model Aggregation		NeurIPS workshop	2023	[PUB]
Augmenting Federated Learning with Pretrained Transformers		NeurIPS workshop	2023	[PUB]
Consensus Optimization at Representation: Improving Personalized Federated Learning via Data-Centric Regularization		NeurIPS workshop	2023	[PUB]
DPZero: Dimension-Independent and Differentially Private Zeroth-Order Optimization		NeurIPS workshop	2023	[PUB]
Leveraging Foundation Models to Improve Lightweight Clients in Federated Learning		NeurIPS workshop	2023	[PUB]
FedML-HE: An Efficient Homomorphic-Encryption-Based Privacy-Preserving Federated Learning System		NeurIPS workshop	2023	[PUB]
Learning Optimizers for Local SGD		NeurIPS workshop	2023	[PUB]
Exploring User-level Gradient Inversion with a Diffusion Prior		NeurIPS workshop	2023	[PUB]
User Inference Attacks on Large Language Models		NeurIPS workshop	2023	[PUB]
FedLDA: Personalized Federated Learning Through Collaborative Linear Discriminant Analysis		NeurIPS workshop	2023	[PUB]
Heterogeneous LoRA for Federated Fine-tuning of On-device Foundation Models		NeurIPS workshop	2023	[PUB]
Backdoor Threats from Compromised Foundation Models to Federated Learning		NeurIPS workshop	2023	[PUB]
MOFL/D: A Federated Multi-objective Learning Framework with Decomposition		NeurIPS workshop	2023	[PUB]
Absolute Variation Distance: an Inversion Attack Evaluation Metric for Federated Learning		NeurIPS workshop	2023	[PUB]
Fed3R: Recursive Ridge Regression for Federated Learning with strong pre-trained models		NeurIPS workshop	2023	[PUB]
FedFN: Feature Normalization for Alleviating Data Heterogeneity Problem in Federated Learning		NeurIPS workshop	2023	[PUB]
Private and Personalized Histogram Estimation in a Federated Setting		NeurIPS workshop	2023	[PUB]
The Aggregation–Heterogeneity Trade-off in Federated Learning	PKU	COLT	2023	[PUB]
FLASH: Automating federated learning using CASH	Rensselaer Polytechnic Institute	UAI	2023	[PUB] [SUPP] [MATERIAL]
Personalized federated domain adaptation for item-to-item recommendation	AWS AI Labs	UAI	2023	[PUB] [PDF] [SUPP] [MATERIAL] [CODE]
Fed-LAMB: Layer-wise and Dimension-wise Locally Adaptive Federated Learning	Baidu Research	UAI	2023	[PUB] [PDF] [SUPP] [MATERIAL]
Federated learning of models pre-trained on different features with consensus graphs	IBM Research	UAI	2023	[PUB] [SUPP] [MATERIAL] [CODE]
Fast Heterogeneous Federated Learning with Hybrid Client Selection	NWPU	UAI	2023	[PUB] [SUPP] [MATERIAL] [PDF]
Learning To Invert: Simple Adaptive Attacks for Gradient Inversion in Federated Learning	Cornell University	UAI	2023	[PUB] [PDF] [SUPP] [MATERIAL] [CODE]
Dynamic Regularized Sharpness Aware Minimization in Federated Learning: Approaching Global Consistency and Smooth Landscape	The University of Sydney	ICML	2023	[PUB] [PDF] [SLIDES]
Analysis of Error Feedback in Federated Non-Convex Optimization with Biased Compression: Fast Convergence and Partial Participation	LinkedIn Ads	ICML	2023	[PUB] [PDF]
FedHPO-Bench: A Benchmark Suite for Federated Hyperparameter Optimization	Alibaba Group	ICML	2023	[PUB] [PDF] [CODE]
Federated Conformal Predictors for Distributed Uncertainty Quantification	MIT	ICML	2023	[PUB] [PDF] [CODE]
Federated Adversarial Learning: A Framework with Convergence Analysis	UBC	ICML	2023	[PUB] [PDF]
Federated Heavy Hitter Recovery under Linear Sketching	Google Research	ICML	2023	[PUB] [PDF] [CODE]
Doubly Adversarial Federated Bandits	London School of Economics and Political Science	ICML	2023	[PUB] [PDF] [CODE]
Achieving Linear Speedup in Non-IID Federated Bilevel Learning	UC	ICML	2023	[PUB] [PDF]
One-Shot Federated Conformal Prediction	Université Paris-Saclay	ICML	2023	[PUB] [PDF] [CODE]
Federated Online and Bandit Convex Optimization	TTIC	ICML	2023	[PUB]
Federated Linear Contextual Bandits with User-level Differential Privacy	The Pennsylvania State University	ICML	2023	[PUB] [PDF]
Vertical Federated Graph Neural Network for Recommender System	NUS	ICML	2023	[PUB] [PDF] [CODE]
Communication-Efficient Federated Hypergradient Computation via Aggregated Iterative Differentiation	University at Buffalo	ICML	2023	[PUB] [PDF]
Towards Understanding Ensemble Distillation in Federated Learning	KAIST	ICML	2023	[PUB]
Personalized Subgraph Federated Learning	KAIST	ICML	2023	[PUB] [PDF] [CODE]
Conformal Prediction for Federated Uncertainty Quantification Under Label Shift	Lagrange Mathematics and Computing Research Center; CMAP	ICML	2023	[PUB] [PDF]
Secure Federated Correlation Test and Entropy Estimation	CMU	ICML	2023	[PUB] [PDF]
Out-of-Distribution Generalization of Federated Learning via Implicit Invariant Relationships	JLU	ICML	2023	[PUB] [CODE]
Personalized Federated Learning under Mixture of Distributions	UCLA	ICML	2023	[PUB] [PDF] [CODE]
FedDisco: Federated Learning with Discrepancy-Aware Collaboration	SJTU	ICML	2023	[PUB] [PDF] [CODE]
Anchor Sampling for Federated Learning with Partial Client Participation	Purdue University	ICML	2023	[PUB] [PDF] [CODE]
Private Federated Learning with Autotuned Compression	JHU; Google	ICML	2023	[PUB] [PDF]
Fast Federated Machine Unlearning with Nonlinear Functional Theory	Auburn University	ICML	2023	[PUB]
On the Convergence of Federated Averaging with Cyclic Client Participation	CMU	ICML	2023	[PUB] [PDF]
Revisiting Weighted Aggregation in Federated Learning with Neural Networks	ZJU	ICML	2023	[PUB] [PDF] [CODE]
The Blessing of Heterogeneity in Federated Q-Learning: Linear Speedup and Beyond	CMU	ICML	2023	[PUB] [PDF] [SLIDES]
GuardHFL: Privacy Guardian for Heterogeneous Federated Learning	UESTC; NTU	ICML	2023	[PUB]
Flash: Concept Drift Adaptation in Federated Learning	University of Massachusetts	ICML	2023	[PUB]
DoCoFL: Downlink Compression for Cross-Device Federated Learning	VMware Research; Technion	ICML	2023	[PUB] [PDF]
FeDXL: Provable Federated Learning for Deep X-Risk Optimization	Texas A&M University	ICML	2023	[PUB] [PDF] [CODE]
No One Idles: Efficient Heterogeneous Federated Learning with Parallel Edge and Server Computation	HIT	ICML	2023	[PUB] [CODE]
Personalized Federated Learning with Inferred Collaboration Graphs	SJTU	ICML	2023	[PUB] [CODE]
Optimizing the Collaboration Structure in Cross-Silo Federated Learning	UIUC	ICML	2023	[PUB] [PDF] [CODE] [SLIDES]
TabLeak: Tabular Data Leakage in Federated Learning	ETH Zurich	ICML	2023	[PUB] [PDF] [CODE]
FedCR: Personalized Federated Learning Based on Across-Client Common Representation with Conditional Mutual Information Regularization	SJTU	ICML	2023	[PUB] [CODE]
Fed-CBS: A Heterogeneity-Aware Client Sampling Mechanism for Federated Learning via Class-Imbalance Reduction	Duke University	ICML	2023	[PUB] [PDF]
Privacy-Aware Compression for Federated Learning Through Numerical Mechanism Design	Meta AI	ICML	2023	[PUB] [PDF] [CODE]
SRATTA: Sample Re-ATTribution Attack of Secure Aggregation in Federated Learning	Owkin Inc.	ICML	2023	[PUB] [PDF] [CODE]
Improving the Model Consistency of Decentralized Federated Learning	THU	ICML	2023	[PUB] [PDF]
Efficient Personalized Federated Learning via Sparse Model-Adaptation	Alibaba Group	ICML	2023	[PUB] [PDF] [CODE]
From Noisy Fixed-Point Iterations to Private ADMM for Centralized and Federated Learning	Univ. Lille	ICML	2023	[PUB] [PDF] [CODE]
LeadFL: Client Self-Defense against Model Poisoning in Federated Learning	TUD	ICML	2023	[PUB] [CODE]
Chameleon: Adapting to Peer Images for Planting Durable Backdoors in Federated Learning	HKUST	ICML	2023	[PUB] [PDF] [CODE]
FedVS: Straggler-Resilient and Privacy-Preserving Vertical Federated Learning for Split Models	HKUST	ICML	2023	[PUB] [PDF]
FedBR: Improving Federated Learning on Heterogeneous Data via Local Learning Bias Reduction	CUHK; The Shenzhen Institute of Artificial Intelligence and Robotics for Society	ICML	2023	[PUB] [PDF] [CODE]
Towards Unbiased Training in Federated Open-world Semi-supervised Learning	PolyU	ICML	2023	[PUB] [PDF] [SLIDES]
Cocktail Party Attack: Breaking Aggregation-Based Privacy in Federated Learning Using Independent Component Analysis	Georgia Tech; Meta AI	ICML	2023	[PUB] [PDF]
Surrogate Model Extension (SME): A Fast and Accurate Weight Update Attack on Federated Learning	KU Leuven	ICML	2023	[PUB] [PDF] [CODE]
Fair yet Asymptotically Equal Collaborative Learning	NUS	ICML	2023	[PUB] [PDF] [CODE]
Sketching for First Order Method: Efficient Algorithm for Low-Bandwidth Channel and Vulnerability	Adobe Research	ICML	2023	[PUB] [PDF]
Adversarial Collaborative Learning on Non-IID Features	UC Berkeley; NUS	ICML	2023	[PUB]
XTab: Cross-table Pretraining for Tabular Transformers	EPFL; Cornell University; AWS	ICML	2023	[PUB] [PDF] [CODE]
Momentum Ensures Convergence of SIGNSGD under Weaker Assumptions	NUDT	ICML	2023	[PUB]
Byzantine-Robust Learning on Heterogeneous Data via Gradient Splitting	Key Lab of Intelligent Computing Based Big Data of Zhejiang Province; ZJU; Sony Al	ICML	2023	[PUB] [PDF] [CODE]
LESS-VFL: Communication-Efficient Feature Selection for Vertical Federated Learning	Rensselaer Polytechnic Institute	ICML	2023	[PUB] [PDF]
FedAvg Converges to Zero Training Loss Linearly for Overparameterized Multi-Layer Neural Networks	University of Minnesota	ICML	2023	[PUB]
Addressing Budget Allocation and Revenue Allocation in Data Market Environments Using an Adaptive Sampling Algorithm	University of Chicago	ICML	2023	[PUB] [PDF] [CODE]
Ensemble and continual federated learning for classification tasks.	Universidade de Santiago de Compostela	Mach Learn	2023	[PUB] [PDF]
FAC-fed: Federated adaptation for fairness and concept drift aware stream classification	Leibniz University of Hannover	Mach Learn	2023	[PUB]
Robust federated learning under statistical heterogeneity via hessian-weighted aggregation	Deakin University	Mach Learn	2023	[PUB]
FedLab: A Flexible Federated Learning Framework	UESTC; Peng Cheng Lab	JMLR	2023	[PUB] [PDF] [CODE]
Memory-Based Optimization Methods for Model-Agnostic Meta-Learning and Personalized Federated Learning	TAMU	JMLR	2023	[PUB] [PDF] [CODE]
A First Look into the Carbon Footprint of Federated Learning	University of Cambridge	JMLR	2023	[PUB] [PDF]
Attacks against Federated Learning Defense Systems and their Mitigation	The University of Newcastle	JMLR	2023	[PUB] [CODE]
A General Theory for Federated Optimization with Asynchronous and Heterogeneous Clients Updates	Universit ́e Cˆ ote d’Azur	JMLR	2023	[PUB] [PDF] [CODE]
Tighter Regret Analysis and Optimization of Online Federated Learning	Hanyang University	TPAMI	2023	[PUB] [PDF]
Efficient Federated Learning Via Local Adaptive Amended Optimizer With Linear Speedup	University of Sydney	TPAMI	2023	[PDF]
Federated Learning Via Inexact ADMM.	BJTU	TPAMI	2023	[PUB] [PDF] [CODE]
FedIPR: Ownership Verification for Federated Deep Neural Network Models	SJTU	TPAMI	2023	[PUB] [PDF] [CODE] [解读]
Decentralized Federated Averaging	NUDT	TPAMI	2023	[PUB] [PDF]
Personalized Federated Learning with Feature Alignment and Classifier Collaboration	THU	ICLR	2023	[PUB] [CODE]
MocoSFL: enabling cross-client collaborative self-supervised learning	ASU	ICLR	2023	[PUB] [CODE]
Single-shot General Hyper-parameter Optimization for Federated Learning	IBM	ICLR	2023	[PUB] [PDF] [CODE]
Where to Begin? Exploring the Impact of Pre-Training and Initialization in Federated	Facebook	ICLR	2023	[PUB] [PDF] [CODE]
FedExP: Speeding up Federated Averaging via Extrapolation	CMU	ICLR	2023	[PUB] [PDF] [CODE]
Turning the Curse of Heterogeneity in Federated Learning into a Blessing for Out-of-Distribution Detection	MSU	ICLR	2023	[PUB] [CODE]
DASHA: Distributed Nonconvex Optimization with Communication Compression and Optimal Oracle Complexity	KAUST	ICLR	2023	[PUB] [PDF] [CODE]
Machine Unlearning of Federated Clusters	University of Illinois	ICLR	2023	[PUB] [PDF] [CODE]
Federated Neural Bandits	NUS	ICLR	2023	[PUB] [PDF] [CODE]
FedFA: Federated Feature Augmentation	ETH Zurich	ICLR	2023	[PUB] [PDF] [CODE]
Federated Learning as Variational Inference: A Scalable Expectation Propagation Approach	CMU	ICLR	2023	[PUB] [PDF] [CODE]
Better Generative Replay for Continual Federated Learning	University of Virginia	ICLR	2023	[PUB] [CODE]
Federated Learning from Small Datasets	IKIM	ICLR	2023	[PUB] [PDF]
Federated Nearest Neighbor Machine Translation	USTC	ICLR	2023	[PUB] [PDF]
Meta Knowledge Condensation for Federated Learning	A*STAR	ICLR	2023	[PUB] [PDF]
Test-Time Robust Personalization for Federated Learning	EPFL	ICLR	2023	[PUB] [PDF] [CODE]
DepthFL : Depthwise Federated Learning for Heterogeneous Clients	SNU	ICLR	2023	[PUB]
Towards Addressing Label Skews in One-Shot Federated Learning	NUS	ICLR	2023	[PUB] [CODE]
Towards Understanding and Mitigating Dimensional Collapse in Heterogeneous Federated Learning	NUS	ICLR	2023	[PUB] [PDF] [CODE]
Panning for Gold in Federated Learning: Targeted Text Extraction under Arbitrarily Large-Scale Aggregation	UMD	ICLR	2023	[PUB] [CODE]
SWIFT: Rapid Decentralized Federated Learning via Wait-Free Model Communication	UMD	ICLR	2023	[PUB] [PDF] [CODE]
Private Federated Learning Without a Trusted Server: Optimal Algorithms for Convex Losses	USC	ICLR	2023	[PUB] [PDF] [CODE]
Effective passive membership inference attacks in federated learning against overparameterized models	Purdue University	ICLR	2023	[PUB]
FiT: Parameter Efficient Few-shot Transfer Learning for Personalized and Federated Image Classification	University of Cambridge	ICLR	2023	[PUB] [PDF] [CODE]
Multimodal Federated Learning via Contrastive Representation Ensemble	THU	ICLR	2023	[PUB] [PDF] [CODE]
Faster federated optimization under second-order similarity	Princeton University	ICLR	2023	[PUB] [PDF] [CODE]
FedSpeed: Larger Local Interval, Less Communication Round, and Higher Generalization Accuracy	University of Sydney	ICLR	2023	[PUB] [CODE]
The Best of Both Worlds: Accurate Global and Personalized Models through Federated Learning with Data-Free Hyper-Knowledge Distillation	utexas	ICLR	2023	[PUB] [PDF] [CODE]
PerFedMask: Personalized Federated Learning with Optimized Masking Vectors	UBC	ICLR	2023	[PUB] [CODE]
EPISODE: Episodic Gradient Clipping with Periodic Resampled Corrections for Federated Learning with Heterogeneous Data	GMU	ICLR	2023	[PUB] [CODE]
FedDAR: Federated Domain-Aware Representation Learning	Harvard	ICLR	2023	[PUB] [PDF] [CODE]
Share Your Representation Only: Guaranteed Improvement of the Privacy-Utility Tradeoff in Federated Learning	upenn	ICLR	2023	[PUB] [CODE]
FLIP: A Provable Defense Framework for Backdoor Mitigation in Federated Learning	Purdue University	ICLR	2023	[PUB] [PDF] [CODE]
Generalization Bounds for Federated Learning: Fast Rates, Unparticipating Clients and Unbounded Losses	RUC	ICLR	2023	[PUB]
Efficient Federated Domain Translation	Purdue University	ICLR	2023	[PUB] [CODE]
On the Importance and Applicability of Pre-Training for Federated Learning	OSU	ICLR	2023	[PUB] [PDF] [CODE]
Decepticons: Corrupted Transformers Breach Privacy in Federated Learning for Language Models	UMD	ICLR	2023	[PUB] [PDF] [CODE]
A Statistical Framework for Personalized Federated Learning and Estimation: Theory, Algorithms, and Privacy	UCLA	ICLR	2023	[PUB] [PDF]
Instance-wise Batch Label Restoration via Gradients in Federated Learning	BUAA	ICLR	2023	[PUB] [CODE]
Data-Free One-Shot Federated Learning Under Very High Statistical Heterogeneity	College of William and Mary	ICLR	2023	[PUB]
CANIFE: Crafting Canaries for Empirical Privacy Measurement in Federated Learning	University of Warwick	ICLR	2023	[PUB] [PDF] [CODE]
Sparse Random Networks for Communication-Efficient Federated Learning	Stanford	ICLR	2023	[PUB] [PDF] [CODE]
Combating Exacerbated Heterogeneity for Robust Decentralized Models	HKBU	ICLR	2023	[PUB] [CODE]
Hyperparameter Optimization through Neural Network Partitioning	University of Cambridge	ICLR	2023	[PUB] [PDF]
Does Decentralized Learning with Non-IID Unlabeled Data Benefit from Self Supervision?	MIT	ICLR	2023	[PUB] [PDF] [CODE]
Variance Reduction is an Antidote to Byzantines: Better Rates, Weaker Assumptions and Communication Compression as a Cherry on the Top	mbzuai	ICLR	2023	[PUB] [PDF] [CODE]
Dual Diffusion Implicit Bridges for Image-to-Image Translation	Stanford	ICLR	2023	[PUB] [PDF] [CODE]
An accurate, scalable and verifiable protocol for federated differentially private averaging	INRIA Lille	Mach Learn	2022	[PUB] [PDF]
Federated online clustering of bandits.	CUHK	UAI	2022	[PUB] [PDF] [CODE]
Privacy-aware compression for federated data analysis.	Meta AI	UAI	2022	[PUB] [PDF] [CODE]
Faster non-convex federated learning via global and local momentum.	UTEXAS	UAI	2022	[PUB] [PDF]
Fedvarp: Tackling the variance due to partial client participation in federated learning.	CMU	UAI	2022	[PUB] [PDF]
SASH: Efficient secure aggregation based on SHPRG for federated learning	CAS; CASTEST	UAI	2022	[PUB] [PDF]
Bayesian federated estimation of causal effects from observational data	NUS	UAI	2022	[PUB] [PDF]
Communication-Efficient Randomized Algorithm for Multi-Kernel Online Federated Learning	Hanyang University	TPAMI	2022	[PUB]
Lazily Aggregated Quantized Gradient Innovation for Communication-Efficient Federated Learning	ZJU	TPAMI	2022	[PUB] [CODE]
Communication Acceleration of Local Gradient Methods via an Accelerated Primal-Dual Algorithm with an Inexact Prox	Moscow Institute of Physics and Technology	NeurIPS	2022	[PUB] [PDF]
LAMP: Extracting Text from Gradients with Language Model Priors	ETHZ	NeurIPS	2022	[PUB] [CODE]
FedAvg with Fine Tuning: Local Updates Lead to Representation Learning	utexas	NeurIPS	2022	[PUB] [PDF]
On Convergence of FedProx: Local Dissimilarity Invariant Bounds, Non-smoothness and Beyond	NUIST	NeurIPS	2022	[PUB] [PDF]
Improved Differential Privacy for SGD via Optimal Private Linear Operators on Adaptive Streams	WISC	NeurIPS	2022	[PUB] [CODE]
Decentralized Gossip-Based Stochastic Bilevel Optimization over Communication Networks	Columbia University	NeurIPS	2022	[PUB] [PDF]
Asymptotic Behaviors of Projected Stochastic Approximation: A Jump Diffusion Perspective	PKU	NeurIPS	2022	[PUB]
Subspace Recovery from Heterogeneous Data with Non-isotropic Noise	Stanford	NeurIPS	2022	[PUB] [PDF]
EF-BV: A Unified Theory of Error Feedback and Variance Reduction Mechanisms for Biased and Unbiased Compression in Distributed Optimization	KAUST	NeurIPS	2022	[PUB] [PDF]
On-Demand Sampling: Learning Optimally from Multiple Distributions	UC Berkeley	NeurIPS	2022	[PUB] [CODE]
Improved Utility Analysis of Private CountSketch	ITU	NeurIPS	2022	[PUB] [PDF] [CODE]
Rate-Distortion Theoretic Bounds on Generalization Error for Distributed Learning	HUAWEI	NeurIPS	2022	[PUB] [CODE]
Decentralized Local Stochastic Extra-Gradient for Variational Inequalities	phystech	NeurIPS	2022	[PUB] [PDF]
BEER: Fast O(1/T) Rate for Decentralized Nonconvex Optimization with Communication Compression	Princeton	NeurIPS	2022	[PUB] [PDF] [CODE]
Escaping Saddle Points with Bias-Variance Reduced Local Perturbed SGD for Communication Efficient Nonconvex Distributed Learning	The University of Tokyo	NeurIPS	2022	[PUB] [PDF]
Near-Optimal Collaborative Learning in Bandits	INRIA; Inserm	NeurIPS	2022	[PUB] [PDF] [CODE]
Distributed Methods with Compressed Communication for Solving Variational Inequalities, with Theoretical Guarantees	phystech	NeurIPS	2022	[PUB] [PDF]
Towards Optimal Communication Complexity in Distributed Non-Convex Optimization	TTIC	NeurIPS	2022	[PUB] [CODE]
FedPop: A Bayesian Approach for Personalised Federated Learning	Skoltech	NeurIPS	2022	[PUB] [PDF]
Fairness in Federated Learning via Core-Stability	UIUC	NeurIPS	2022	[PUB] [CODE]
SecureFedYJ: a safe feature Gaussianization protocol for Federated Learning	Sorbonne Université	NeurIPS	2022	[PUB] [PDF]
FedRolex: Model-Heterogeneous Federated Learning with Rolling Submodel Extraction	MSU	NeurIPS	2022	[PUB] [CODE]
On Sample Optimality in Personalized Collaborative and Federated Learning	INRIA	NeurIPS	2022	[PUB]
DReS-FL: Dropout-Resilient Secure Federated Learning for Non-IID Clients via Secret Data Sharing	HKUST	NeurIPS	2022	[PUB] [PDF]
FairVFL: A Fair Vertical Federated Learning Framework with Contrastive Adversarial Learning	THU	NeurIPS	2022	[PUB]
Variance Reduced ProxSkip: Algorithm, Theory and Application to Federated Learning	KAUST	NeurIPS	2022	[PUB] [PDF]
VF-PS: How to Select Important Participants in Vertical Federated Learning, Efficiently and Securely?	WHU	NeurIPS	2022	[PUB] [CODE]
DENSE: Data-Free One-Shot Federated Learning	ZJU	NeurIPS	2022	[PUB] [PDF]
CalFAT: Calibrated Federated Adversarial Training with Label Skewness	ZJU	NeurIPS	2022	[PUB] [PDF]
SAGDA: Achieving O(ϵ−2) Communication Complexity in Federated Min-Max Learning	OSU	NeurIPS	2022	[PUB] [PDF]
Taming Fat-Tailed (“Heavier-Tailed” with Potentially Infinite Variance) Noise in Federated Learning	OSU	NeurIPS	2022	[PUB] [PDF]
Personalized Federated Learning towards Communication Efficiency, Robustness and Fairness	PKU	NeurIPS	2022	[PUB]
Federated Submodel Optimization for Hot and Cold Data Features	SJTU	NeurIPS	2022	[PUB]
BooNTK: Convexifying Federated Learning using Bootstrapped Neural Tangent Kernels	UC Berkeley	NeurIPS	2022	[PUB] [PDF]
Byzantine-tolerant federated Gaussian process regression for streaming data	PSU	NeurIPS	2022	[PUB] [CODE]
SoteriaFL: A Unified Framework for Private Federated Learning with Communication Compression	CMU	NeurIPS	2022	[PUB] [PDF]
Coresets for Vertical Federated Learning: Regularized Linear Regression and K-Means Clustering	Yale	NeurIPS	2022	[PUB] [PDF] [CODE]
Communication Efficient Federated Learning for Generalized Linear Bandits	University of Virginia	NeurIPS	2022	[PUB] [CODE]
Recovering Private Text in Federated Learning of Language Models	Princeton	NeurIPS	2022	[PUB] [PDF] [CODE]
Federated Learning from Pre-Trained Models: A Contrastive Learning Approach	UTS	NeurIPS	2022	[PUB] [PDF]
Global Convergence of Federated Learning for Mixed Regression	Northeastern University	NeurIPS	2022	[PUB] [PDF]
Resource-Adaptive Federated Learning with All-In-One Neural Composition	JHU	NeurIPS	2022	[PUB]
Self-Aware Personalized Federated Learning	Amazon	NeurIPS	2022	[PUB] [PDF]
A Communication-efficient Algorithm with Linear Convergence for Federated Minimax Learning	Northeastern University	NeurIPS	2022	[PUB] [PDF]
An Adaptive Kernel Approach to Federated Learning of Heterogeneous Causal Effects	NUS	NeurIPS	2022	[PUB]
Sharper Convergence Guarantees for Asynchronous SGD for Distributed and Federated Learning	EPFL	NeurIPS	2022	[PUB] [PDF]
Personalized Online Federated Multi-Kernel Learning	UCI	NeurIPS	2022	[PUB]
SemiFL: Semi-Supervised Federated Learning for Unlabeled Clients with Alternate Training	Duke University	NeurIPS	2022	[PUB] [PDF] [CODE]
A Unified Analysis of Federated Learning with Arbitrary Client Participation	IBM	NeurIPS	2022	[PUB] [PDF]
Preservation of the Global Knowledge by Not-True Distillation in Federated Learning	KAIST	NeurIPS	2022	[PUB] [PDF] [CODE]
FedSR: A Simple and Effective Domain Generalization Method for Federated Learning	University of Oxford	NeurIPS	2022	[PUB] [CODE]
Factorized-FL: Personalized Federated Learning with Parameter Factorization & Similarity Matching	KAIST	NeurIPS	2022	[PUB] [PDF] [CODE]
A Simple and Provably Efficient Algorithm for Asynchronous Federated Contextual Linear Bandits	UC	NeurIPS	2022	[PUB] [PDF]
Learning to Attack Federated Learning: A Model-based Reinforcement Learning Attack Framework	Tulane University	NeurIPS	2022	[PUB]
On Privacy and Personalization in Cross-Silo Federated Learning	CMU	NeurIPS	2022	[PUB] [PDF]
A Coupled Design of Exploiting Record Similarity for Practical Vertical Federated Learning	NUS	NeurIPS	2022	[PUB] [PDF] [CODE]
FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Healthcare Settings	Owkin	NeurIPS Datasets and Benchmarks	2022	[PUB] [CODE]
A Tree-based Model Averaging Approach for Personalized Treatment Effect Estimation from Heterogeneous Data Sources	University of Pittsburgh	ICML	2022	[PUB] [PDF] [CODE]
Fast Composite Optimization and Statistical Recovery in Federated Learning	SJTU	ICML	2022	[PUB] [PDF] [CODE]
Personalization Improves Privacy-Accuracy Tradeoffs in Federated Learning	NYU	ICML	2022	[PUB] [PDF] [CODE]
The Fundamental Price of Secure Aggregation in Differentially Private Federated Learning	Stanford; Google Research	ICML	2022	[PUB] [PDF] [CODE] [SLIDE]
The Poisson Binomial Mechanism for Unbiased Federated Learning with Secure Aggregation	Stanford; Google Research	ICML	2022	[PUB] [PDF] [CODE]
DisPFL: Towards Communication-Efficient Personalized Federated Learning via Decentralized Sparse Training	USTC	ICML	2022	[PUB] [PDF] [CODE]
FedNew: A Communication-Efficient and Privacy-Preserving Newton-Type Method for Federated Learning	University of Oulu	ICML	2022	[PUB] [PDF] [CODE]
DAdaQuant: Doubly-adaptive quantization for communication-efficient Federated Learning	University of Cambridge	ICML	2022	[PUB] [PDF] [SLIDE] [CODE]
Accelerated Federated Learning with Decoupled Adaptive Optimization	Auburn University	ICML	2022	[PUB] [PDF]
Federated Reinforcement Learning: Linear Speedup Under Markovian Sampling	Georgia Tech	ICML	2022	[PUB] [PDF]
Multi-Level Branched Regularization for Federated Learning	Seoul National University	ICML	2022	[PUB] [PDF] [CODE] [PAGE]
FedScale: Benchmarking Model and System Performance of Federated Learning at Scale	University of Michigan	ICML	2022	[PUB] [PDF] [CODE]
Federated Learning with Positive and Unlabeled Data	XJTU	ICML	2022	[PUB] [PDF] [CODE]
Deep Neural Network Fusion via Graph Matching with Applications to Model Ensemble and Federated Learning	SJTU	ICML	2022	[PUB] [CODE]
Orchestra: Unsupervised Federated Learning via Globally Consistent Clustering	University of Michigan	ICML	2022	[PUB] [PDF] [CODE]
Disentangled Federated Learning for Tackling Attributes Skew via Invariant Aggregation and Diversity Transferring	USTC	ICML	2022	[PUB] [PDF] [CODE] [SLIDE] [解读]
Architecture Agnostic Federated Learning for Neural Networks	The University of Texas at Austin	ICML	2022	[PUB] [PDF] [SLIDE]
Personalized Federated Learning through Local Memorization	Inria	ICML	2022	[PUB] [PDF] [CODE]
Proximal and Federated Random Reshuffling	KAUST	ICML	2022	[PUB] [PDF] [CODE]
Federated Learning with Partial Model Personalization	University of Washington	ICML	2022	[PUB] [PDF] [CODE]
Generalized Federated Learning via Sharpness Aware Minimization	University of South Florida	ICML	2022	[PUB] [PDF]
FedNL: Making Newton-Type Methods Applicable to Federated Learning	KAUST	ICML	2022	[PUB] [PDF] [VIDEO] [SLIDE]
Federated Minimax Optimization: Improved Convergence Analyses and Algorithms	CMU	ICML	2022	[PUB] [PDF] [SLIDE]
Virtual Homogeneity Learning: Defending against Data Heterogeneity in Federated Learning	Hong Kong Baptist University	ICML	2022	[PUB] [PDF] [CODE] [解读]
FedNest: Federated Bilevel, Minimax, and Compositional Optimization	University of Michigan	ICML	2022	[PUB] [PDF] [CODE]
EDEN: Communication-Efficient and Robust Distributed Mean Estimation for Federated Learning	VMware Research	ICML	2022	[PUB] [PDF] [CODE]
Communication-Efficient Adaptive Federated Learning	Pennsylvania State University	ICML	2022	[PUB] [PDF]
ProgFed: Effective, Communication, and Computation Efficient Federated Learning by Progressive Training	CISPA Helmholz Center for Information Security	ICML	2022	[PUB] [PDF] [SLIDE] [CODE]
Fishing for User Data in Large-Batch Federated Learning via Gradient Magnification	University of Maryland	ICML	2022	[PUB] [PDF] [CODE]
Anarchic Federated Learning	The Ohio State University	ICML	2022	[PUB] [PDF]
QSFL: A Two-Level Uplink Communication Optimization Framework for Federated Learning	Nankai University	ICML	2022	[PUB] [CODE]
Bitwidth Heterogeneous Federated Learning with Progressive Weight Dequantization	KAIST	ICML	2022	[PUB] [PDF]
Neural Tangent Kernel Empowered Federated Learning	NC State University	ICML	2022	[PUB] [PDF] [CODE]
Understanding Clipping for Federated Learning: Convergence and Client-Level Differential Privacy	UMN	ICML	2022	[PUB] [PDF]
Personalized Federated Learning via Variational Bayesian Inference	CAS	ICML	2022	[PUB] [PDF] [SLIDE] [UC.]
Federated Learning with Label Distribution Skew via Logits Calibration	ZJU	ICML	2022	[PUB]
Neurotoxin: Durable Backdoors in Federated Learning	Southeast University;Princeton	ICML	2022	[PUB] [PDF] [CODE]
Resilient and Communication Efficient Learning for Heterogeneous Federated Systems	Michigan State University	ICML	2022	[PUB]
Minibatch vs Local SGD with Shuffling: Tight Convergence Bounds and Beyond	KAIST	ICLR (oral)	2022	[PUB] [CODE]
Bayesian Framework for Gradient Leakage	ETH Zurich	ICLR	2022	[PUB] [PDF] [CODE]
Federated Learning from only unlabeled data with class-conditional-sharing clients	The University of Tokyo; CUHK	ICLR	2022	[PUB] [CODE]
FedChain: Chained Algorithms for Near-Optimal Communication Cost in Federated Learning	CMU; University of Illinois at Urbana-Champaign; University of Washington	ICLR	2022	[PUB] [PDF]
Acceleration of Federated Learning with Alleviated Forgetting in Local Training	THU	ICLR	2022	[PUB] [PDF] [CODE]
FedPara: Low-rank Hadamard Product for Communicatkion-Efficient Federated Learning	POSTECH	ICLR	2022	[PUB] [PDF] [CODE]
An Agnostic Approach to Federated Learning with Class Imbalance	University of Pennsylvania	ICLR	2022	[PUB] [CODE]
Efficient Split-Mix Federated Learning for On-Demand and In-Situ Customization	Michigan State University; The University of Texas at Austin	ICLR	2022	[PUB] [PDF] [CODE]
Robbing the Fed: Directly Obtaining Private Data in Federated Learning with Modified Models	University of Maryland; NYU	ICLR	2022	[PUB] [PDF] [CODE]
ZeroFL: Efficient On-Device Training for Federated Learning with Local Sparsity	University of Cambridge; University of Oxford	ICLR	2022	[PUB] [PDF]
Diverse Client Selection for Federated Learning via Submodular Maximization	Intel; CMU	ICLR	2022	[PUB] [CODE]
Recycling Model Updates in Federated Learning: Are Gradient Subspaces Low-Rank?	Purdue	ICLR	2022	[PUB] [PDF] [CODE]
Diurnal or Nocturnal? Federated Learning of Multi-branch Networks from Periodically Shifting Distributions	University of Maryland; Google	ICLR	2022	[PUB] [CODE]
Towards Model Agnostic Federated Learning Using Knowledge Distillation	EPFL	ICLR	2022	[PUB] [PDF] [CODE]
Divergence-aware Federated Self-Supervised Learning	NTU; SenseTime	ICLR	2022	[PUB] [PDF] [CODE]
What Do We Mean by Generalization in Federated Learning?	Stanford; Google	ICLR	2022	[PUB] [PDF] [CODE]
FedBABU: Toward Enhanced Representation for Federated Image Classification	KAIST	ICLR	2022	[PUB] [PDF] [CODE]
Byzantine-Robust Learning on Heterogeneous Datasets via Bucketing	EPFL	ICLR	2022	[PUB] [PDF] [CODE]
Improving Federated Learning Face Recognition via Privacy-Agnostic Clusters	Aibee	ICLR Spotlight	2022	[PUB] [PDF] [PAGE] [解读]
Hybrid Local SGD for Federated Learning with Heterogeneous Communications	University of Texas; Pennsylvania State University	ICLR	2022	[PUB]
On Bridging Generic and Personalized Federated Learning for Image Classification	The Ohio State University	ICLR	2022	[PUB] [PDF] [CODE]
Minibatch vs Local SGD with Shuffling: Tight Convergence Bounds and Beyond	KAIST; MIT	ICLR	2022	[PUB] [PDF]
One-Shot Federated Learning: Theoretical Limits and Algorithms to Achieve Them.		JMLR	2021	[PUB] [CODE]
Constrained differentially private federated learning for low-bandwidth devices		UAI	2021	[PUB] [PDF]
Federated stochastic gradient Langevin dynamics		UAI	2021	[PUB] [PDF]
Federated Learning Based on Dynamic Regularization	BU; ARM	ICLR	2021	[PUB] [PDF] [CODE]
Achieving Linear Speedup with Partial Worker Participation in Non-IID Federated Learning	The Ohio State University	ICLR	2021	[PUB] [PDF]
HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous Clients	Duke University	ICLR	2021	[PUB] [PDF] [CODE]
FedMix: Approximation of Mixup under Mean Augmented Federated Learning	KAIST	ICLR	2021	[PUB] [PDF]
Federated Learning via Posterior Averaging: A New Perspective and Practical Algorithms	CMU; Google	ICLR	2021	[PUB] [PDF] [CODE]
Adaptive Federated Optimization	Google	ICLR	2021	[PUB] [PDF] [CODE]
Personalized Federated Learning with First Order Model Optimization	Stanford; NVIDIA	ICLR	2021	[PUB] [PDF] [CODE] [UC.]
FedBN: Federated Learning on Non-IID Features via Local Batch Normalization	Princeton	ICLR	2021	[PUB] [PDF] [CODE]
FedBE: Making Bayesian Model Ensemble Applicable to Federated Learning	The Ohio State University	ICLR	2021	[PUB] [PDF] [CODE]
Federated Semi-Supervised Learning with Inter-Client Consistency & Disjoint Learning	KAIST	ICLR	2021	[PUB] [PDF] [CODE]
KD3A: Unsupervised Multi-Source Decentralized Domain Adaptation via Knowledge Distillation	ZJU	ICML	2021	[PUB] [PDF] [CODE] [解读]
Gradient Disaggregation: Breaking Privacy in Federated Learning by Reconstructing the User Participant Matrix	Harvard University	ICML	2021	[PUB] [PDF] [VIDEO] [CODE]
FL-NTK: A Neural Tangent Kernel-based Framework for Federated Learning Analysis	PKU; Princeton	ICML	2021	[PUB] [PDF] [VIDEO]
Personalized Federated Learning using Hypernetworks	Bar-Ilan University; NVIDIA	ICML	2021	[PUB] [PDF] [CODE] [PAGE] [VIDEO] [解读]
Federated Composite Optimization	Stanford; Google	ICML	2021	[PUB] [PDF] [CODE] [VIDEO] [SLIDE]
Exploiting Shared Representations for Personalized Federated Learning	University of Texas at Austin; University of Pennsylvania	ICML	2021	[PUB] [PDF] [CODE] [VIDEO]
Data-Free Knowledge Distillation for Heterogeneous Federated Learning	Michigan State University	ICML	2021	[PUB] [PDF] [CODE] [VIDEO]
Federated Continual Learning with Weighted Inter-client Transfer	KAIST	ICML	2021	[PUB] [PDF] [CODE] [VIDEO]
Federated Deep AUC Maximization for Hetergeneous Data with a Constant Communication Complexity	The University of Iowa	ICML	2021	[PUB] [PDF] [CODE] [VIDEO]
Bias-Variance Reduced Local SGD for Less Heterogeneous Federated Learning	The University of Tokyo	ICML	2021	[PUB] [PDF] [VIDEO]
Federated Learning of User Verification Models Without Sharing Embeddings	Qualcomm	ICML	2021	[PUB] [PDF] [VIDEO]
Clustered Sampling: Low-Variance and Improved Representativity for Clients Selection in Federated Learning	Accenture	ICML	2021	[PUB] [PDF] [CODE] [VIDEO]
Ditto: Fair and Robust Federated Learning Through Personalization	CMU; Facebook AI	ICML	2021	[PUB] [PDF] [CODE] [VIDEO]
Heterogeneity for the Win: One-Shot Federated Clustering	CMU	ICML	2021	[PUB] [PDF] [VIDEO]
The Distributed Discrete Gaussian Mechanism for Federated Learning with Secure Aggregation	Google	ICML	2021	[PUB] [PDF] [CODE] [VIDEO]
Debiasing Model Updates for Improving Personalized Federated Training	BU; Arm	ICML	2021	[PUB] [CODE] [VIDEO]
One for One, or All for All: Equilibria and Optimality of Collaboration in Federated Learning	Toyota; Berkeley; Cornell University	ICML	2021	[PUB] [PDF] [CODE] [VIDEO]
CRFL: Certifiably Robust Federated Learning against Backdoor Attacks	UIUC; IBM	ICML	2021	[PUB] [PDF] [CODE] [VIDEO]
Federated Learning under Arbitrary Communication Patterns	Indiana University; Amazon	ICML	2021	[PUB] [VIDEO]
CANITA: Faster Rates for Distributed Convex Optimization with Communication Compression	CMU	NeurIPS	2021	[PUB] [PDF]
Boosting with Multiple Sources	Google	NeurIPS	2021	[PUB]
DRIVE: One-bit Distributed Mean Estimation	VMware	NeurIPS	2021	[PUB] [CODE]
Gradient Driven Rewards to Guarantee Fairness in Collaborative Machine Learning	NUS	NeurIPS	2021	[PUB] [CODE]
Gradient Inversion with Generative Image Prior	POSTECH	NeurIPS	2021	[PUB] [PDF] [CODE]
Distributed Machine Learning with Sparse Heterogeneous Data	University of Oxford	NeurIPS	2021	[PUB] [PDF]
Renyi Differential Privacy of The Subsampled Shuffle Model In Distributed Learning	UCLA	NeurIPS	2021	[PUB] [PDF]
Sageflow: Robust Federated Learning against Both Stragglers and Adversaries	KAIST	NeurIPS	2021	[PUB]
CAFE: Catastrophic Data Leakage in Vertical Federated Learning	Rensselaer Polytechnic Institute; IBM Research	NeurIPS	2021	[PUB] [CODE]
Fault-Tolerant Federated Reinforcement Learning with Theoretical Guarantee	NUS	NeurIPS	2021	[PUB] [PDF] [CODE]
Optimality and Stability in Federated Learning: A Game-theoretic Approach	Cornell University	NeurIPS	2021	[PUB] [PDF] [CODE]
QuPeD: Quantized Personalization via Distillation with Applications to Federated Learning	UCLA	NeurIPS	2021	[PUB] [PDF] [CODE] [解读]
The Skellam Mechanism for Differentially Private Federated Learning	Google Research; CMU	NeurIPS	2021	[PUB] [PDF] [CODE]
No Fear of Heterogeneity: Classifier Calibration for Federated Learning with Non-IID Data	NUS; Huawei	NeurIPS	2021	[PUB] [PDF]
STEM: A Stochastic Two-Sided Momentum Algorithm Achieving Near-Optimal Sample and Communication Complexities for Federated Learning	UMN	NeurIPS	2021	[PUB] [PDF]
Subgraph Federated Learning with Missing Neighbor Generation	Emory; UBC; Lehigh University	NeurIPS	2021	[PUB] [PDF] [CODE] [解读]
Evaluating Gradient Inversion Attacks and Defenses in Federated Learning	Princeton	NeurIPS	2021	[PUB] [PDF] [CODE]
Personalized Federated Learning With Gaussian Processes	Bar-Ilan University	NeurIPS	2021	[PUB] [PDF] [CODE]
Differentially Private Federated Bayesian Optimization with Distributed Exploration	MIT; NUS	NeurIPS	2021	[PUB] [PDF] [CODE]
Parameterized Knowledge Transfer for Personalized Federated Learning	PolyU	NeurIPS	2021	[PUB] [PDF] [CODE]
Federated Reconstruction: Partially Local Federated Learning	Google Research	NeurIPS	2021	[PUB] [PDF] [CODE] [UC.]
Fast Federated Learning in the Presence of Arbitrary Device Unavailability	THU; Princeton; MIT	NeurIPS	2021	[PUB] [PDF] [CODE]
FL-WBC: Enhancing Robustness against Model Poisoning Attacks in Federated Learning from a Client Perspective	Duke University; Accenture Labs	NeurIPS	2021	[PUB] [PDF] [CODE]
FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout	KAUST; Samsung AI Center	NeurIPS	2021	[PUB] [PDF]
Linear Convergence in Federated Learning: Tackling Client Heterogeneity and Sparse Gradients	University of Pennsylvania	NeurIPS	2021	[PUB] [PDF] [VIDEO]
Federated Multi-Task Learning under a Mixture of Distributions	INRIA; Accenture Labs	NeurIPS	2021	[PUB] [PDF] [CODE]
Federated Graph Classification over Non-IID Graphs	Emory	NeurIPS	2021	[PUB] [PDF] [CODE] [解读]
Federated Hyperparameter Tuning: Challenges, Baselines, and Connections to Weight-Sharing	CMU; Hewlett Packard Enterprise	NeurIPS	2021	[PUB] [PDF] [CODE]
On Large-Cohort Training for Federated Learning	Google; CMU	NeurIPS	2021	[PUB] [PDF] [CODE]
DeepReduce: A Sparse-tensor Communication Framework for Federated Deep Learning	KAUST; Columbia University; University of Central Florida	NeurIPS	2021	[PUB] [PDF] [CODE]
PartialFed: Cross-Domain Personalized Federated Learning via Partial Initialization	Huawei	NeurIPS	2021	[PUB] [VIDEO]
Federated Split Task-Agnostic Vision Transformer for COVID-19 CXR Diagnosis	KAIST	NeurIPS	2021	[PUB] [PDF]
Addressing Algorithmic Disparity and Performance Inconsistency in Federated Learning	THU; Alibaba; Weill Cornell Medicine	NeurIPS	2021	[PUB] [PDF] [CODE]
Federated Linear Contextual Bandits	The Pennsylvania State University; Facebook; University of Virginia	NeurIPS	2021	[PUB] [PDF] [CODE]
Few-Round Learning for Federated Learning	KAIST	NeurIPS	2021	[PUB]
Breaking the centralized barrier for cross-device federated learning	EPFL; Google Research	NeurIPS	2021	[PUB] [CODE] [VIDEO]
Federated-EM with heterogeneity mitigation and variance reduction	Ecole Polytechnique; Google Research	NeurIPS	2021	[PUB] [PDF]
Delayed Gradient Averaging: Tolerate the Communication Latency for Federated Learning	MIT; Amazon; Google	NeurIPS	2021	[PUB] [PAGE] [SLIDE]
FedDR – Randomized Douglas-Rachford Splitting Algorithms for Nonconvex Federated Composite Optimization	University of North Carolina at Chapel Hill; IBM Research	NeurIPS	2021	[PUB] [PDF] [CODE]
Federated Adversarial Domain Adaptation	BU; Columbia University; Rutgers University	ICLR	2020	[PUB] [PDF] [CODE]
DBA: Distributed Backdoor Attacks against Federated Learning	ZJU; IBM Research	ICLR	2020	[PUB] [CODE]
Fair Resource Allocation in Federated Learning	CMU; Facebook AI	ICLR	2020	[PUB] [PDF] [CODE]
Federated Learning with Matched Averaging	University of Wisconsin-Madison; IBM Research	ICLR	2020	[PUB] [PDF] [CODE]
Differentially Private Meta-Learning	CMU	ICLR	2020	[PUB] [PDF]
Generative Models for Effective ML on Private, Decentralized Datasets	Google	ICLR	2020	[PUB] [PDF] [CODE]
On the Convergence of FedAvg on Non-IID Data	PKU	ICLR	2020	[PUB] [PDF] [CODE] [解读]
FedBoost: A Communication-Efficient Algorithm for Federated Learning	Google	ICML	2020	[PUB] [VIDEO]
FetchSGD: Communication-Efficient Federated Learning with Sketching	UC Berkeley; Johns Hopkins University; Amazon	ICML	2020	[PUB] [PDF] [VIDEO] [CODE]
SCAFFOLD: Stochastic Controlled Averaging for Federated Learning	EPFL; Google	ICML	2020	[PUB] [PDF] [VIDEO] [UC.] [解读]
Federated Learning with Only Positive Labels	Google	ICML	2020	[PUB] [PDF] [VIDEO]
From Local SGD to Local Fixed-Point Methods for Federated Learning	Moscow Institute of Physics and Technology; KAUST	ICML	2020	[PUB] [PDF] [SLIDE] [VIDEO]
Acceleration for Compressed Gradient Descent in Distributed and Federated Optimization	KAUST	ICML	2020	[PUB] [PDF] [SLIDE] [VIDEO]
Differentially-Private Federated Linear Bandits	MIT	NeurIPS	2020	[PUB] [PDF] [CODE]
Federated Principal Component Analysis	University of Cambridge; Quine Technologies	NeurIPS	2020	[PUB] [PDF] [CODE]
FedSplit: an algorithmic framework for fast federated optimization	UC Berkeley	NeurIPS	2020	[PUB] [PDF]
Federated Bayesian Optimization via Thompson Sampling	NUS; MIT	NeurIPS	2020	[PUB] [PDF] [CODE]
Lower Bounds and Optimal Algorithms for Personalized Federated Learning	KAUST	NeurIPS	2020	[PUB] [PDF]
Robust Federated Learning: The Case of Affine Distribution Shifts	UC Santa Barbara; MIT	NeurIPS	2020	[PUB] [PDF] [CODE]
An Efficient Framework for Clustered Federated Learning	UC Berkeley; DeepMind	NeurIPS	2020	[PUB] [PDF] [CODE]
Distributionally Robust Federated Averaging	Pennsylvania State University	NeurIPS	2020	[PUB] [PDF] [CODE]
Personalized Federated Learning with Moreau Envelopes	The University of Sydney	NeurIPS	2020	[PUB] [PDF] [CODE]
Personalized Federated Learning with Theoretical Guarantees: A Model-Agnostic Meta-Learning Approach	MIT; UT Austin	NeurIPS	2020	[PUB] [PDF] [UC.]
Group Knowledge Transfer: Federated Learning of Large CNNs at the Edge	USC	NeurIPS	2020	[PUB] [PDF] [CODE] [解读]
Tackling the Objective Inconsistency Problem in Heterogeneous Federated Optimization	CMU; Princeton	NeurIPS	2020	[PUB] [PDF] [CODE] [UC.]
Attack of the Tails: Yes, You Really Can Backdoor Federated Learning	University of Wisconsin-Madison	NeurIPS	2020	[PUB] [PDF]
Federated Accelerated Stochastic Gradient Descent	Stanford	NeurIPS	2020	[PUB] [PDF] [CODE] [VIDEO]
Inverting Gradients - How easy is it to break privacy in federated learning?	University of Siegen	NeurIPS	2020	[PUB] [PDF] [CODE]
Ensemble Distillation for Robust Model Fusion in Federated Learning	EPFL	NeurIPS	2020	[PUB] [PDF] [CODE]
Throughput-Optimal Topology Design for Cross-Silo Federated Learning	INRIA	NeurIPS	2020	[PUB] [PDF] [CODE]
Bayesian Nonparametric Federated Learning of Neural Networks	IBM	ICML	2019	[PUB] [PDF] [CODE]
Analyzing Federated Learning through an Adversarial Lens	Princeton; IBM	ICML	2019	[PUB] [PDF] [CODE]
Agnostic Federated Learning	Google	ICML	2019	[PUB] [PDF]
cpSGD: Communication-efficient and differentially-private distributed SGD	Princeton; Google	NeurIPS	2018	[PUB] [PDF]
Federated Multi-Task Learning	Stanford; USC; CMU	NeurIPS	2017	[PUB] [PDF] [CODE]

fl in top dm conference and journal

Federated Learning papers accepted by top DM(Data Mining) conference and journal, Including KDD(ACM SIGKDD Conference on Knowledge Discovery and Data Mining) and WSDM(Web Search and Data Mining).

KDD 2023(Research Track, Applied Data Science track, Workshop), 2022(Research Track, Applied Data Science track), 2021, 2020
WSDM 2024, 2023, 2022, 2021, 2019

fl in top dm conference and journal

Title	Affiliation	Venue	Year	Materials
User Consented Federated Recommender System Against Personalized Attribute Inference Attack	HKUST	WSDM	2024	[PUB] [PDF] [CODE]
Guardian: Guarding against Gradient Leakage with Provable Defense for Federated Learning	ECNU	WSDM	2024	[PUB]
Privacy Matters: Vertical Federated Linear Contextual Bandits for Privacy Protected Recommendation	University of Cambridge	KDD	2023	[PUB] [PDF]
FedDefender: Client-Side Attack-Tolerant Federated Learning	KAIST	KDD	2023	[PUB] [PDF] [CODE]
FedAPEN: Personalized Cross-silo Federated Learning with Adaptability to Statistical Heterogeneity	ZJU	KDD	2023	[PUB] [CODE]
FedPseudo: Privacy-Preserving Pseudo Value-Based Deep Learning Models for Federated Survival Analysis	UMBC	KDD	2023	[PUB] [PDF]
ShapleyFL: Robust Federated Learning Based on Shapley Value	ZJU	KDD	2023	[PUB] [CODE]
Federated Few-shot Learning	University of Virginia	KDD	2023	[PUB] [PDF] [CODE]
Theoretical Convergence Guaranteed Resource-Adaptive Federated Learning with Mixed Heterogeneity	SDU	KDD	2023	[PUB]
Personalized Federated Learning with Parameter Propagation	UIUC	KDD	2023	[PUB]
Serverless Federated AUPRC Optimization for Multi-Party Collaborative Imbalanced Data Mining	University of Pittsburgh	KDD	2023	[PUB] [PDF] [CODE]
CriticalFL: A Critical Learning Periods Augmented Client Selection Framework for Efficient Federated Learning	SUNY-Binghamton University	KDD	2023	[PUB] [PDF]
FLAMES2Graph: An Interpretable Federated Multivariate Time Series Classification Framework	L3S Research Center	KDD	2023	[PUB] [PDF]
FedCP: Separating Feature Information for Personalized Federated Learning via Conditional Policy	SJTU	KDD	2023	[PUB] [PDF] [CODE]
Navigating Alignment for Non-identical Client Class Sets: A Label Name-Anchored Federated Learning Framework	UCSD	KDD	2023	[PUB] [PDF] [CODE]
DM-PFL: Hitchhiking Generic Federated Learning for Efficient Shift-Robust Personalization	BUAA	KDD	2023	[PUB] [CODE]
FS-REAL: Towards Real-World Cross-Device Federated Learning	Alibaba Group	KDD	2023	[PUB] [PDF]
FedMultimodal: A Benchmark for Multimodal Federated Learning	USC	KDD	2023	[PUB] [PDF] [CODE]
PrivateRec: Differentially Private Model Training and Online Serving for Federated News Recommendation	RUC	KDD	2023	[PUB] [PDF] [NEWS]
Revisiting Personalized Federated Learning: Robustness Against Backdoor Attacks	HKUST; Alibaba Group	KDD	2023	[PUB] [PDF] [CODE]
UA-FedRec: Untargeted Attack on Federated News Recommendation	USTC	KDD	2023	[PUB] [PDF] [CODE]
International Workshop on Federated Learning for Distributed Data Mining	MSU	KDD Workshop Summaries	2023	[PUB] [PAGE]
Is Normalization Indispensable for Multi-domain Federated Learning?		KDD workshop	2023	[PUB]
Distributed Personalized Empirical Risk Minimization.		KDD workshop	2023	[PUB]
Once-for-All Federated Learning: Learning From and Deploying to Heterogeneous Clients.		KDD workshop	2023	[PUB]
SparseVFL: Communication-Efficient Vertical Federated Learning Based on Sparsification of Embeddings and Gradients.		KDD workshop	2023	[PUB]
Optimization of User Resources in Federated Learning for Urban Sensing Applications		KDD workshop	2023	[PUB]
FedLEGO: Enabling Heterogenous Model Cooperation via Brick Reassembly in Federated Learning.		KDD workshop	2023	[PUB]
Federated Graph Analytics with Differential Privacy.		KDD workshop	2023	[PUB]
Scaling Distributed Multi-task Reinforcement Learning with Experience Sharing.		KDD workshop	2023	[PUB]
Uncertainty Quantification in Federated Learning for Heterogeneous Health Data		KDD workshop	2023	[PUB]
A Systematic Evaluation of Federated Learning on Biomedical Natural Language Processing.		KDD workshop	2023	[PUB]
Taming Heterogeneity to Deal with Test-Time Shift in Federated Learning.		KDD workshop	2023	[PUB]
Federated Blood Supply Chain Demand Forecasting: A Case Study.		KDD workshop	2023	[PUB]
Stochastic Clustered Federated Learning.		KDD workshop	2023	[PUB]
A Privacy-Preserving Hybrid Federated Learning Framework for Financial Crime Detection.		KDD workshop	2023	[PUB]
Exploring the Efficacy of Data-Decoupled Federated Learning for Image Classification and Medical Imaging Analysis.		KDD workshop	2023	[PUB]
FedNoisy: A Federated Noisy Label Learning Benchmark		KDD workshop	2023	[PUB]
Asynchronous Decentralized Federated Lifelong Learning for Landmark Localization in Medical Imaging		KDD workshop	2023	[PUB]
Federated learning for competing risk analysis in healthcare.		KDD workshop	2023	[PUB]
Federated Threat Detection for Smart Home IoT rules.		KDD workshop	2023	[PUB]
Federated Unlearning for On-Device Recommendation	UQ	WSDM	2023	[PUB] [PDF]
Collaboration Equilibrium in Federated Learning	THU	KDD	2022	[PUB] [PDF] [CODE]
Connected Low-Loss Subspace Learning for a Personalization in Federated Learning	Ulsan National Institute of Science and Technology	KDD	2022	[PUB] [PDF] [CODE]
FedMSplit: Correlation-Adaptive Federated Multi-Task Learning across Multimodal Split Networks	University of Virginia	KDD	2022	[PUB]
Communication-Efficient Robust Federated Learning with Noisy Labels	University of Pittsburgh	KDD	2022	[PUB] [PDF]
FLDetector: Detecting Malicious Clients in Federated Learning via Checking Model-Updates Consistency	USTC	KDD	2022	[PUB] [PDF] [CODE]
Practical Lossless Federated Singular Vector Decomposition Over Billion-Scale Data	HKUST	KDD	2022	[PUB] [PDF] [CODE]
FedWalk: Communication Efficient Federated Unsupervised Node Embedding with Differential Privacy	SJTU	KDD	2022	[PUB] [PDF]
FederatedScope-GNN: Towards a Unified, Comprehensive and Efficient Platform for Federated Graph Learning	Alibaba	KDD (Best Paper Award)	2022	[PUB] [PDF] [CODE]
Fed-LTD: Towards Cross-Platform Ride Hailing via Federated Learning to Dispatch	BUAA	KDD	2022	[PUB] [PDF] [解读]
Felicitas: Federated Learning in Distributed Cross Device Collaborative Frameworks	USTC	KDD	2022	[PUB] [PDF]
No One Left Behind: Inclusive Federated Learning over Heterogeneous Devices	Renmin University of China	KDD	2022	[PUB] [PDF]
FedAttack: Effective and Covert Poisoning Attack on Federated Recommendation via Hard Sampling	THU	KDD	2022	[PUB] [PDF] [CODE]
PipAttack: Poisoning Federated Recommender Systems for Manipulating Item Promotion	The University of Queensland	WSDM	2022	[PUB] [PDF]
Fed2: Feature-Aligned Federated Learning	George Mason University; Microsoft; University of Maryland	KDD	2021	[PUB] [PDF]
FedRS: Federated Learning with Restricted Softmax for Label Distribution Non-IID Data	Nanjing University	KDD	2021	[PUB] [CODE]
Federated Adversarial Debiasing for Fair and Trasnferable Representations	Michigan State University	KDD	2021	[PUB] [PAGE] [CODE] [SLIDE]
Cross-Node Federated Graph Neural Network for Spatio-Temporal Data Modeling	USC	KDD	2021	[PUB] [CODE] [解读]
AsySQN: Faster Vertical Federated Learning Algorithms with Better Computation Resource Utilization	Xidian University;JD Tech	KDD	2021	[PUB] [PDF]
FLOP: Federated Learning on Medical Datasets using Partial Networks	Duke University	KDD	2021	[PUB] [PDF] [CODE]
A Practical Federated Learning Framework for Small Number of Stakeholders	ETH Zürich	WSDM	2021	[PUB] [CODE]
Federated Deep Knowledge Tracing	USTC	WSDM	2021	[PUB] [CODE]
FedFast: Going Beyond Average for Faster Training of Federated Recommender Systems	University College Dublin	KDD	2020	[PUB] [VIDEO]
Federated Doubly Stochastic Kernel Learning for Vertically Partitioned Data	JD Tech	KDD	2020	[PUB] [PDF] [VIDEO]
Federated Online Learning to Rank with Evolution Strategies	Facebook AI Research	WSDM	2019	[PUB] [CODE]

fl in top secure conference and journal

Federated Learning papers accepted by top Secure conference and journal, Including S&P(IEEE Symposium on Security and Privacy), CCS(Conference on Computer and Communications Security), USENIX Security(Usenix Security Symposium) and NDSS(Network and Distributed System Security Symposium).

fl in top secure conference and journal

Title	Affiliation	Venue	Year	Materials
Turning Privacy-preserving Mechanisms against Federated Learning	University of Pavia	CCS	2023	[PUB] [PDF]
MESAS: Poisoning Defense for Federated Learning Resilient against Adaptive Attackers	University of Würzburg	CCS	2023	[PUB]
martFL: Enabling Utility-Driven Data Marketplace with a Robust and Verifiable Federated Learning Architecture	THU	CCS	2023	[PUB] [PDF] [CODE]
Unraveling the Connections between Privacy and Certified Robustness in Federated Learning Against Poisoning Attacks	UIUC	CCS	2023	[PUB] [PDF]
Poster: Verifiable Data Valuation with Strong Fairness in Horizontal Federated Learning	NSYSU	CCS	2023	[PUB]
Poster: Bridging Trust Gaps: Data Usage Transparency in Federated Data Ecosystems	RWTH Aachen University	CCS	2023	[PUB]
Every Vote Counts: Ranking-Based Training of Federated Learning to Resist Poisoning Attacks	University of Massachusetts Amherst	USENIX Security	2023	[PUB] [PDF]
PrivateFL: Accurate, Differentially Private Federated Learning via Personalized Data Transformation	JHU	USENIX Security	2023	[PUB] [CODE]
Gradient Obfuscation Gives a False Sense of Security in Federated Learning	NCSU	USENIX Security	2023	[PUB] [PDF] [CODE]
FedVal: Different good or different bad in federated learning	AI Sweden	USENIX Security	2023	[PUB] [PDF] [CODE]
Securing Federated Sensitive Topic Classification against Poisoning Attacks	IMDEA Networks Institute	NDSS	2023	[PUB] [PDF] [CODE]
PPA: Preference Profiling Attack Against Federated Learning	NJUST	NDSS	2023	[PUB] [PDF]
Turning Privacy-preserving Mechanisms against Federated Learning	University of Pavia; TU Delft; University of Padua; Radboud University	CCS	2023	[PUB] [PDF] [CODE]
CERBERUS: Exploring Federated Prediction of Security Events	UCL London	CCS	2022	[PUB] [PDF]
EIFFeL: Ensuring Integrity for Federated Learning	UW-Madison	CCS	2022	[PUB] [PDF]
Eluding Secure Aggregation in Federated Learning via Model Inconsistency	SPRING Lab; EPFL	CCS	2022	[PUB] [PDF] [CODE]
Federated Boosted Decision Trees with Differential Privacy	University of Warwick	CCS	2022	[PUB] [PDF] [CODE]
FedRecover: Recovering from Poisoning Attacks in Federated Learning using Historical Information	Duke University	S&P	2023	[PUB] [PDF]
Scalable and Privacy-Preserving Federated Principal Component Analysis	EPFL; Tune Insight SA	S&P	2023	[PUB] [PDF]
SafeFL: MPC-friendly Framework for Private and Robust Federated Learning	TU Darmstadt	S&P Workshop	2023	[PUB]
On the Pitfalls of Security Evaluation of Robust Federated Learning.	umass	S&P Workshop	2023	[PUB]
BayBFed: Bayesian Backdoor Defense for Federated Learning	TU Darmstadt; UTSA	S&P	2023	[PUB] [PDF]
3DFed: Adaptive and Extensible Framework for Covert Backdoor Attack in Federated Learning	PolyU	S&P	2023	[PUB] [CODE]
RoFL: Robustness of Secure Federated Learning.	ETH Zurich	S&P	2023	[PUB] [PDF] [CODE]
Flamingo: Multi-Round Single-Server Secure Aggregation with Applications to Private Federated Learning.	upenn	S&P	2023	[PUB] [CODE]
ELSA: Secure Aggregation for Federated Learning with Malicious Actors.		S&P	2023
Private, Efficient, and Accurate: Protecting Models Trained by Multi-party Learning with Differential Privacy	Fudan University	S&P	2023	[PUB] [PDF]
Back to the Drawing Board: A Critical Evaluation of Poisoning Attacks on Production Federated Learning	University of Massachusetts	S&P	2022	[PUB] [VIDEO]
SIMC: ML Inference Secure Against Malicious Clients at Semi-Honest Cost	Microsoft Research	USENIX Security	2022	[PUB] [PDF] [CODE] [VIDEO] [SUPP]
Efficient Differentially Private Secure Aggregation for Federated Learning via Hardness of Learning with Errors	University of Vermont	USENIX Security	2022	[PUB] [SLIDE] [VIDEO]
Label Inference Attacks Against Vertical Federated Learning	ZJU	USENIX Security	2022	[PUB] [SLIDE] [CODE] [VIDEO]
FLAME: Taming Backdoors in Federated Learning	Technical University of Darmstadt	USENIX Security	2022	[PUB] [SLIDE] [PDF] [VIDEO]
Local and Central Differential Privacy for Robustness and Privacy in Federated Learning	University at Buffalo, SUNY	NDSS	2022	[PUB] [PDF] [VIDEO] [UC.]
Interpretable Federated Transformer Log Learning for Cloud Threat Forensics	University of the Incarnate Word	NDSS	2022	[PUB] [VIDEO] [UC.]
FedCRI: Federated Mobile Cyber-Risk Intelligence	Technical University of Darmstadt	NDSS	2022	[PUB] [VIDEO]
DeepSight: Mitigating Backdoor Attacks in Federated Learning Through Deep Model Inspection	Technical University of Darmstadt	NDSS	2022	[PUB] [PDF] [VIDEO]
Private Hierarchical Clustering in Federated Networks	NUS	CCS	2021	[PUB] [PDF]
FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping	Duke University	NDSS	2021	[PUB] [PDF] [CODE] [VIDEO] [SLIDE]
POSEIDON: Privacy-Preserving Federated Neural Network Learning	EPFL	NDSS	2021	[PUB] [VIDEO]
Manipulating the Byzantine: Optimizing Model Poisoning Attacks and Defenses for Federated Learning	University of Massachusetts Amherst	NDSS	2021	[PUB] [CODE] [VIDEO]
SAFELearn: Secure Aggregation for private FEderated Learning	TU Darmstadt	S&P Workshop	2021	[PUB]
Local Model Poisoning Attacks to Byzantine-Robust Federated Learning	The Ohio State University	USENIX Security	2020	[PUB] [PDF] [CODE] [VIDEO] [SLIDE]
A Reliable and Accountable Privacy-Preserving Federated Learning Framework using the Blockchain	University of Kansas	CCS (Poster)	2019	[PUB]
IOTFLA : A Secured and Privacy-Preserving Smart Home Architecture Implementing Federated Learning	Université du Québéc á Montréal	S&P Workshop	2019	[PUB]
Comprehensive Privacy Analysis of Deep Learning: Passive and Active White-box Inference Attacks against Centralized and Federated Learning	University of Massachusetts Amherst	S&P	2019	[PUB] [VIDEO] [SLIDE] [CODE]
Practical Secure Aggregation for Privacy Preserving Machine Learning	Google	CCS	2017	[PUB] [PDF] [解读] [UC.] [UC]

fl in top cv conference and journal

Federated Learning papers accepted by top CV(computer vision) conference and journal, Including CVPR(Computer Vision and Pattern Recognition), ICCV(IEEE International Conference on Computer Vision), ECCV(European Conference on Computer Vision), MM(ACM International Conference on Multimedia), IJCV(International Journal of Computer Vision).

fl in top cv conference and journal

Title	Affiliation	Venue	Year	Materials
FedCE: Personalized Federated Learning Method based on Clustering Ensembles	BJTU	MM	2023	[PUB]
FedVQA: Personalized Federated Visual Question Answering over Heterogeneous Scenes	Leiden University	MM	2023	[PUB]
Towards Fast and Stable Federated Learning: Confronting Heterogeneity via Knowledge Anchor	XJTU	MM	2023	[PUB] [PDF] [CODE]
Federated Deep Multi-View Clustering with Global Self-Supervision	UESTC	MM	2023	[PUB] [PDF]
FedAA: Using Non-sensitive Modalities to Improve Federated Learning while Preserving Image Privacy	ZJU	MM	2023	[PUB]
Prototype-guided Knowledge Transfer for Federated Unsupervised Cross-modal Hashing	SDNU	MM	2023	[PUB] [CODE]
Joint Local Relational Augmentation and Global Nash Equilibrium for Federated Learning with Non-IID Data	ZJU	MM	2023	[PUB] [PDF]
FedCD: A Classifier Debiased Federated Learning Framework for Non-IID Data	BUPT	MM	2023	[PUB]
Federated Learning with Label-Masking Distillation	UCAS	MM	2023	[PUB] [CODE]
Cross-Silo Prototypical Calibration for Federated Learning with Non-IID Data	SDU	MM	2023	[PUB] [PDF] [CODE]
A Four-Pronged Defense Against Byzantine Attacks in Federated Learning	HUST	MM	2023	[PUB] [PDF]
Client-Adaptive Cross-Model Reconstruction Network for Modality-Incomplete Multimodal Federated Learning	CAS; Peng Cheng Laboratory; UCAS	MM	2023	[PUB]
FedGH: Heterogeneous Federated Learning with Generalized Global Header	NKU	MM	2023	[PUB] [PDF] [CODE]
Cuing Without Sharing: A Federated Cued Speech Recognition Framework via Mutual Knowledge Distillation	CUHK	MM	2023	[PUB] [PDF] [CODE]
AffectFAL: Federated Active Affective Computing with Non-IID Data	TJUT	MM	2023	[PUB] [CODE]
Improving Federated Person Re-Identification through Feature-Aware Proximity and Aggregation	SZU	MM	2023	[PUB]
Towards Attack-tolerant Federated Learning via Critical Parameter Analysis	KAIST	ICCV	2023	[PUB] [PDF] [CODE] [SUPP]
Efficient Model Personalization in Federated Learning via Client-Specific Prompt Generation	NTU; NVIDIA	ICCV	2023	[PUB] [PDF] [SUPP]
Generative Gradient Inversion via Over-Parameterized Networks in Federated Learning	A*STAR	ICCV	2023	[PUB] [CODE] [SUPP]
GPFL: Simultaneously Learning Global and Personalized Feature Information for Personalized Federated Learning	SJTU	ICCV	2023	[PUB] [PDF] [CODE] [SUPP]
Workie-Talkie: Accelerating Federated Learning by Overlapping Computing and Communications via Contrastive Regularization	University of Houston	ICCV	2023	[PUB] [SUPP]
PGFed: Personalize Each Client's Global Objective for Federated Learning	University of Pittsburgh	ICCV	2023	[PUB] [PDF] [CODE] [SUPP]
FedPerfix: Towards Partial Model Personalization of Vision Transformers in Federated Learning	UCF	ICCV	2023	[PUB] [PDF] [CODE] [SUPP]
L-DAWA: Layer-wise Divergence Aware Weight Aggregation in Federated Self-Supervised Visual Representation Learning	TCL AI Lab	ICCV	2023	[PUB] [PDF] [SUPP]
FedPD: Federated Open Set Recognition with Parameter Disentanglement	City University of Hong Kong	ICCV	2023	[PUB] [CODE]
TARGET: Federated Class-Continual Learning via Exemplar-Free Distillation	ETH Zurich; Sony AI	ICCV	2023	[PUB] [PDF] [CODE]
Towards Instance-adaptive Inference for Federated Learning	A*STAR	ICCV	2023	[PUB] [PDF] [CODE]
Communication-efficient Federated Learning with Single-Step Synthetic Features Compressor for Faster Convergence	SCU; Engineering Research Center of Machine Learning and Industry Intelligence	ICCV	2023	[PUB] [PDF] [CODE]
zPROBE: Zero Peek Robustness Checks for Federated Learning	Purdue University	ICCV	2023	[PUB] [PDF] [SUPP]
ProtoFL: Unsupervised Federated Learning via Prototypical Distillation	KakaoBank Corp.	ICCV	2023	[PUB] [PDF]
MAS: Towards Resource-Efficient Federated Multiple-Task Learning	Sony AI	ICCV	2023	[PUB] [PDF] [CODE] [SUPP]
FSAR: Federated Skeleton-based Action Recognition with Adaptive Topology Structure and Knowledge Distillation	PKU	ICCV	2023	[PUB] [PDF] [SUPP]
When Do Curricula Work in Federated Learning?	UCSD	ICCV	2023	[PUB] [PDF] [SUPP]
Communication-Efficient Vertical Federated Learning with Limited Overlapping Samples	Duke University	ICCV	2023	[PUB] [PDF] [CODE]
Multi-Metrics Adaptively Identifies Backdoors in Federated Learning	SCUT	ICCV	2023	[PUB] [PDF] [CODE] [SUPP]
No Fear of Classifier Biases: Neural Collapse Inspired Federated Learning with Synthetic and Fixed Classifier	ZJU	ICCV	2023	[PUB] [PDF] [CODE] [SUPP]
FRAug: Tackling Federated Learning with Non-IID Features via Representation Augmentation	Ludwig Maximilian University of Munich; Siemens Technology	ICCV	2023	[PUB] [PDF] [SUPP]
Bold but Cautious: Unlocking the Potential of Personalized Federated Learning through Cautiously Aggressive Collaboration	BUAA	ICCV	2023	[PUB] [PDF] [CODE] [SUPP]
Global Balanced Experts for Federated Long-Tailed Learning	CUHK-Shenzhen	ICCV	2023	[PUB] [CODE] [SUPP]
Knowledge-Aware Federated Active Learning with Non-IID Data	The University of Sydney	ICCV	2023	[PUB] [PDF] [CODE] [SUPP]
Enhancing Privacy Preservation in Federated Learning via Learning Rate Perturbation	BUPT	ICCV	2023	[PUB] [SUPP]
Local or Global: Selective Knowledge Assimilation for Federated Learning with Limited Labels	CMU	ICCV	2023	[PUB] [PDF] [SUPP]
Federated Learning Over Images: Vertical Decompositions and Pre-Trained Backbones Are Difficult to Beat	Rice University	ICCV	2023	[PUB] [PDF] [CODE] [SUPP]
Robust Heterogeneous Federated Learning under Data Corruption	WHU	ICCV	2023	[PUB] [CODE] [SUPP]
Personalized Semantics Excitation for Federated Image Classification	Tulane University	ICCV	2023	[PUB] [CODE]
Reducing Training Time in Cross-Silo Federated Learning Using Multigraph Topology	AIOZ	ICCV	2023	[PUB] [PDF] [CODE] [SUPP]
Window-based Model Averaging Improves Generalization in Heterogeneous Federated Learning.	Politecnico di Torino	ICCV workshop	2023	[PUB] [PDF]
Experience Replay as an Effective Strategy for Optimizing Decentralized Federated Learning.	University of Catania	ICCV workshop	2023	[PUB]
FedRCIL: Federated Knowledge Distillation for Representation based Contrastive Incremental Learning.	Centre for Research and Technology Hellas; University of West Attica	ICCV workshop	2023	[PUB] [CODE]
FedLID: Self-Supervised Federated Learning for Leveraging Limited Image Data.	Centre for Research and Technology Hellas; University of West Attica	ICCV workshop	2023	[PUB]
Rethinking Federated Learning With Domain Shift: A Prototype View	WHU	CVPR	2023	[PUB] [CODE]
Class Balanced Adaptive Pseudo Labeling for Federated Semi-Supervised Learning	ECNU	CVPR	2023	[PUB] [CODE]
DaFKD: Domain-Aware Federated Knowledge Distillation	HUST	CVPR	2023	[PUB] [CODE]
The Resource Problem of Using Linear Layer Leakage Attack in Federated Learning	Purdue University	CVPR	2023	[PUB] [PDF]
FedSeg: Class-Heterogeneous Federated Learning for Semantic Segmentation	ZJU	CVPR	2023	[PUB]
On the Effectiveness of Partial Variance Reduction in Federated Learning With Heterogeneous Data	DTU	CVPR	2023	[PUB] [PDF]
Elastic Aggregation for Federated Optimization	Meituan	CVPR	2023	[PUB]
FedDM: Iterative Distribution Matching for Communication-Efficient Federated Learning	UCLA	CVPR	2023	[PUB] [PDF]
Adaptive Channel Sparsity for Federated Learning Under System Heterogeneity	UM	CVPR	2023	[PUB]
ScaleFL: Resource-Adaptive Federated Learning With Heterogeneous Clients	GaTech	CVPR	2023	[PUB] [CODE]
Reliable and Interpretable Personalized Federated Learning	TJU	CVPR	2023	[PUB]
Federated Domain Generalization With Generalization Adjustment	SJTU	CVPR	2023	[PUB] [CODE]
Make Landscape Flatter in Differentially Private Federated Learning	THU	CVPR	2023	[PUB] [PDF] [CODE]
Confidence-Aware Personalized Federated Learning via Variational Expectation Maximization	KU Leuven	CVPR	2023	[PUB] [PDF] [CODE]
STDLens: Model Hijacking-Resilient Federated Learning for Object Detection	GaTech	CVPR	2023	[PUB] [PDF] [CODE]
Re-Thinking Federated Active Learning Based on Inter-Class Diversity	KAIST	CVPR	2023	[PUB] [PDF] [CODE]
Learning Federated Visual Prompt in Null Space for MRI Reconstruction	A*STAR	CVPR	2023	[PUB] [PDF] [CODE]
Fair Federated Medical Image Segmentation via Client Contribution Estimation	CUHK	CVPR	2023	[PUB] [PDF] [CODE]
Federated Learning With Data-Agnostic Distribution Fusion	NJU	CVPR	2023	[PUB] [CODE]
How To Prevent the Poor Performance Clients for Personalized Federated Learning?	CSU	CVPR	2023	[PUB]
GradMA: A Gradient-Memory-Based Accelerated Federated Learning With Alleviated Catastrophic Forgetting	ECNU	CVPR	2023	[PUB] [PDF] [CODE]
Bias-Eliminating Augmentation Learning for Debiased Federated Learning	NTU	CVPR	2023	[PUB]
Federated Incremental Semantic Segmentation	CAS; UCAS	CVPR	2023	[PUB] [PDF] [CODE]
Asynchronous Federated Continual Learning	University of Padova	CVPR workshop	2023	[PUB] [PDF] [SILDES] [CODE]
Mixed Quantization Enabled Federated Learning To Tackle Gradient Inversion Attacks	UMBC	CVPR workshop	2023	[PUB] [CODE]
OpenFed: A Comprehensive and Versatile Open-Source Federated Learning Framework	Meituan	CVPR workshop	2023	[PUB] [PDF] [CODE]
Federated Learning in Non-IID Settings Aided by Differentially Private Synthetic Data	utexas	CVPR workshop	2023	[PUB] [SUPP] [PDF] [CODE]
TimelyFL: Heterogeneity-Aware Asynchronous Federated Learning With Adaptive Partial Training	USC	CVPR workshop	2023	[PUB] [PDF]
Many-Task Federated Learning: A New Problem Setting and a Simple Baseline	utexas	CVPR workshop	2023	[PUB] [CODE]
Confederated Learning: Going Beyond Centralization	CAS; UCAS	MM	2022	[PUB]
Few-Shot Model Agnostic Federated Learning	WHU	MM	2022	[PUB] [CODE]
Feeling Without Sharing: A Federated Video Emotion Recognition Framework Via Privacy-Agnostic Hybrid Aggregation	TJUT	MM	2022	[PUB]
FedLTN: Federated Learning for Sparse and Personalized Lottery Ticket Networks		ECCV	2022	[PUB] [SUPP]
Auto-FedRL: Federated Hyperparameter Optimization for Multi-Institutional Medical Image Segmentation		ECCV	2022	[PUB] [SUPP] [PDF] [CODE]
Improving Generalization in Federated Learning by Seeking Flat Minima	Politecnico di Torino	ECCV	2022	[PUB] [SUPP] [PDF] [CODE]
AdaBest: Minimizing Client Drift in Federated Learning via Adaptive Bias Estimation		ECCV	2022	[PUB] [SUPP] [PDF] [CODE] [PAGE]
SphereFed: Hyperspherical Federated Learning		ECCV	2022	[PUB] [SUPP] [PDF]
Federated Self-Supervised Learning for Video Understanding		ECCV	2022	[PUB] [PDF] [CODE]
FedVLN: Privacy-Preserving Federated Vision-and-Language Navigation		ECCV	2022	[PUB] [SUPP] [PDF] [CODE]
Addressing Heterogeneity in Federated Learning via Distributional Transformation		ECCV	2022	[PUB] [CODE]
FedX: Unsupervised Federated Learning with Cross Knowledge Distillation	KAIST	ECCV	2022	[PUB] [SUPP] [PDF] [CODE]
Personalizing Federated Medical Image Segmentation via Local Calibration	Xiamen University	ECCV	2022	[PUB] [SUPP] [PDF] [CODE]
ATPFL: Automatic Trajectory Prediction Model Design Under Federated Learning Framework	HIT	CVPR	2022	[PUB]
Rethinking Architecture Design for Tackling Data Heterogeneity in Federated Learning	Stanford	CVPR	2022	[PUB] [SUPP] [PDF] [CODE] [VIDEO]
FedCorr: Multi-Stage Federated Learning for Label Noise Correction	Singapore University of Technology and Design	CVPR	2022	[PUB] [SUPP] [PDF] [CODE] [VIDEO]
FedCor: Correlation-Based Active Client Selection Strategy for Heterogeneous Federated Learning	Duke University	CVPR	2022	[PUB] [SUPP] [PDF]
Layer-Wised Model Aggregation for Personalized Federated Learning	PolyU	CVPR	2022	[PUB] [SUPP] [PDF]
Local Learning Matters: Rethinking Data Heterogeneity in Federated Learning	University of Central Florida	CVPR	2022	[PUB] [SUPP] [PDF] [CODE]
Federated Learning With Position-Aware Neurons	Nanjing University	CVPR	2022	[PUB] [SUPP] [PDF]
RSCFed: Random Sampling Consensus Federated Semi-Supervised Learning	HKUST	CVPR	2022	[PUB] [SUPP] [PDF] [CODE]
Learn From Others and Be Yourself in Heterogeneous Federated Learning	Wuhan University	CVPR	2022	[PUB] [CODE] [VIDEO]
Robust Federated Learning With Noisy and Heterogeneous Clients	Wuhan University	CVPR	2022	[PUB] [SUPP] [CODE]
ResSFL: A Resistance Transfer Framework for Defending Model Inversion Attack in Split Federated Learning	Arizona State University	CVPR	2022	[PUB] [SUPP] [PDF] [CODE]
FedDC: Federated Learning With Non-IID Data via Local Drift Decoupling and Correction	National University of Defense Technology	CVPR	2022	[PUB] [PDF] [CODE] [解读]
Federated Class-Incremental Learning	CAS; Northwestern University; UTS	CVPR	2022	[PUB] [PDF] [CODE]
Fine-Tuning Global Model via Data-Free Knowledge Distillation for Non-IID Federated Learning	PKU; JD Explore Academy; The University of Sydney	CVPR	2022	[PUB] [PDF]
Differentially Private Federated Learning With Local Regularization and Sparsification	CAS	CVPR	2022	[PUB] [PDF]
Auditing Privacy Defenses in Federated Learning via Generative Gradient Leakage	University of Tennessee; Oak Ridge National Laboratory; Google Research	CVPR	2022	[PUB] [PDF] [CODE] [VIDEO]
CD2-pFed: Cyclic Distillation-Guided Channel Decoupling for Model Personalization in Federated Learning	SJTU	CVPR	2022	[PUB] [PDF]
Closing the Generalization Gap of Cross-Silo Federated Medical Image Segmentation	Univ. of Pittsburgh; NVIDIA	CVPR	2022	[PUB] [PDF]
Adaptive Differential Filters for Fast and Communication-Efficient Federated Learning	HHI	CVPR workshop	2022	[PUB] [PDF] [SILDES] [VIDEO]
MPAF: Model Poisoning Attacks to Federated Learning Based on Fake Clients	Duke University	CVPR workshop	2022	[PUB] [PDF] [SILDES] [VIDEO]
Communication-Efficient Federated Data Augmentation on Non-IID Data	UESTC	CVPR workshop	2022	[PUB]
Does Federated Dropout Actually Work?	Stanford	CVPR workshop	2022	[PUB] [VIDEO]
FedIris: Towards More Accurate and Privacy-preserving Iris Recognition via Federated Template Communication	USTC; CRIPAC; CASIA	CVPR workshop	2022	[PUB] [SLIDES] [VIDEO]
Multi-Institutional Collaborations for Improving Deep Learning-Based Magnetic Resonance Image Reconstruction Using Federated Learning	Johns Hopkins University	CVPR	2021	[PUB] [PDF] [CODE]
Model-Contrastive Federated Learning	NUS; UC Berkeley	CVPR	2021	[PUB] [PDF] [CODE] [解读]
FedDG: Federated Domain Generalization on Medical Image Segmentation via Episodic Learning in Continuous Frequency Space	CUHK	CVPR	2021	[PUB] [PDF] [CODE]
Soteria: Provable Defense Against Privacy Leakage in Federated Learning From Representation Perspective	Duke University	CVPR	2021	[PUB] [PDF] [CODE]
Federated Learning for Non-IID Data via Unified Feature Learning and Optimization Objective Alignment	PKU	ICCV	2021	[PUB]
Ensemble Attention Distillation for Privacy-Preserving Federated Learning	University at Buffalo	ICCV	2021	[PUB] [PDF]
Collaborative Unsupervised Visual Representation Learning from Decentralized Data	NTU; SenseTime	ICCV	2021	[PUB] [PDF]
Joint Optimization in Edge-Cloud Continuum for Federated Unsupervised Person Re-identification	NTU	MM	2021	[PUB] [PDF]
Federated Visual Classification with Real-World Data Distribution	MIT; Google	ECCV	2020	[PUB] [PDF] [VIDEO]
InvisibleFL: Federated Learning over Non-Informative Intermediate Updates against Multimedia Privacy Leakages		MM	2020	[PUB]
Performance Optimization of Federated Person Re-identification via Benchmark Analysis `data.`	NTU	MM	2020	[PUB] [PDF] [CODE] [解读]

fl in top nlp conference and journal

Federated Learning papers accepted by top AI and NLP conference and journal, including ACL(Annual Meeting of the Association for Computational Linguistics), NAACL(North American Chapter of the Association for Computational Linguistics), EMNLP(Conference on Empirical Methods in Natural Language Processing) and COLING(International Conference on Computational Linguistics).

fl in top nlp conference and journal

Title	Affiliation	Venue	Year	Materials
Federated Learning of Large Language Models with Parameter-Efficient Prompt Tuning and Adaptive Optimization	Auburn University	EMNLP	2023	[PUB] [PDF] [CODE]
Federated Meta-Learning for Emotion and Sentiment Aware Multi-modal Complaint Identification	IIT Patna	EMNLP	2023	[PUB] [CODE]
FedID: Federated Interactive Distillation for Large-Scale Pretraining Language Models	YNU	EMNLP	2023	[PUB] [CODE]
FedTherapist: Mental Health Monitoring with User-Generated Linguistic Expressions on Smartphones via Federated Learning	KAIST	EMNLP	2023	[PUB] [PDF]
Coordinated Replay Sample Selection for Continual Federated Learning	CMU	EMNLP industry Track	2023	[PUB] [PDF]
Tunable Soft Prompts are Messengers in Federated Learning	SYSU	EMNLP Findings	2023	[PUB] [PDF] [CODE]
Federated Learning for Semantic Parsing: Task Formulation, Evaluation Setup, New Algorithms	OSU	ACL	2023	[PUB] [PDF] [CODE]
FEDLEGAL: The First Real-World Federated Learning Benchmark for Legal NLP	HIT; Peng Cheng Lab	ACL	2023	[PUB] [CODE]
Client-Customized Adaptation for Parameter-Efficient Federated Learning		ACL Findings	2023	[PUB]
Communication Efficient Federated Learning for Multilingual Neural Machine Translation with Adapter		ACL Findings	2023	[PUB] [PDF] [CODE]
Federated Domain Adaptation for Named Entity Recognition via Distilling with Heterogeneous Tag Sets		ACL Findings	2023	[PUB]
FedPETuning: When Federated Learning Meets the Parameter-Efficient Tuning Methods of Pre-trained Language Models		ACL Findings	2023	[PUB]
Federated Learning of Gboard Language Models with Differential Privacy		ACL Industry Track	2023	[PUB] [PDF]
Backdoor Attacks in Federated Learning by Rare Embeddings and Gradient Ensembling	SNU	EMNLP	2022	[PUB] [PDF]
A Federated Approach to Predicting Emojis in Hindi Tweets	University of Alberta	EMNLP	2022	[PUB] [PDF] [CODE]
Federated Model Decomposition with Private Vocabulary for Text Classification	HIT; Peng Cheng Lab	EMNLP	2022	[PUB] [CODE]
Fair NLP Models with Differentially Private Text Encoders	Univ. Lille	EMNLP	2022	[PUB] [PDF] [CODE]
Federated Continual Learning for Text Classification via Selective Inter-client Transfer	DRIMCo GmbH; LMU	EMNLP Findings	2022	[PUB] [PDF] [CODE]
Efficient Federated Learning on Knowledge Graphs via Privacy-preserving Relation Embedding Aggregation `kg.`	Lehigh University	EMNLP Findings	2022	[PUB] [PDF] [CODE]
Dim-Krum: Backdoor-Resistant Federated Learning for NLP with Dimension-wise Krum-Based Aggregation	PKU	EMNLP Findings	2022	[PUB] [PDF]
Scaling Language Model Size in Cross-Device Federated Learning	Google	ACL workshop	2022	[PUB] [PDF]
Intrinsic Gradient Compression for Scalable and Efficient Federated Learning	Oxford	ACL workshop	2022	[PUB] [PDF]
ActPerFL: Active Personalized Federated Learning	Amazon	ACL workshop	2022	[PUB] [PAGE]
FedNLP: Benchmarking Federated Learning Methods for Natural Language Processing Tasks	USC	NAACL	2022	[PUB] [PDF] [CODE]
Federated Learning with Noisy User Feedback	USC; Amazon	NAACL	2022	[PUB] [PDF]
Training Mixed-Domain Translation Models via Federated Learning	Amazon	NAACL	2022	[PUB] [PAGE] [PDF]
Pretrained Models for Multilingual Federated Learning	Johns Hopkins University	NAACL	2022	[PUB] [PDF] [CODE]
Federated Chinese Word Segmentation with Global Character Associations	University of Washington	ACL workshop	2021	[PUB] [CODE]
Efficient-FedRec: Efficient Federated Learning Framework for Privacy-Preserving News Recommendation	USTC	EMNLP	2021	[PUB] [PDF] [CODE] [VIDEO]
Improving Federated Learning for Aspect-based Sentiment Analysis via Topic Memories	CUHK (Shenzhen)	EMNLP	2021	[PUB] [CODE] [VIDEO]
A Secure and Efficient Federated Learning Framework for NLP	University of Connecticut	EMNLP	2021	[PUB] [PDF] [VIDEO]
Distantly Supervised Relation Extraction in Federated Settings	UCAS	EMNLP workshop	2021	[PUB] [PDF] [CODE]
Federated Learning with Noisy User Feedback	USC; Amazon	NAACL workshop	2021	[PUB] [PDF]
An Investigation towards Differentially Private Sequence Tagging in a Federated Framework	Universität Hamburg	NAACL workshop	2021	[PUB]
Understanding Unintended Memorization in Language Models Under Federated Learning	Google	NAACL workshop	2021	[PUB] [PDF]
FedED: Federated Learning via Ensemble Distillation for Medical Relation Extraction	CAS	EMNLP	2020	[PUB] [VIDEO] [解读]
Empirical Studies of Institutional Federated Learning For Natural Language Processing	Ping An Technology	EMNLP workshop	2020	[PUB]
Federated Learning for Spoken Language Understanding	PKU	COLING	2020	[PUB]
Two-stage Federated Phenotyping and Patient Representation Learning	Boston Children’s Hospital Harvard Medical School	ACL workshop	2019	[PUB] [PDF] [CODE] [UC.]

fl in top ir conference and journal

Federated Learning papers accepted by top Information Retrieval conference and journal, including SIGIR(Annual International ACM SIGIR Conference on Research and Development in Information Retrieval).

SIGIR 2023, 2022, 2021, 2020

fl in top ir conference and journal

Title	Affiliation	Venue	Year	Materials
Personalized Federated Relation Classification over Heterogeneous Texts	NUDT	SIGIR	2023	[PUB]
Fine-Grained Preference-Aware Personalized Federated POI Recommendation with Data Sparsity	SDU	SIGIR	2023	[PUB]
Manipulating Federated Recommender Systems: Poisoning with Synthetic Users and Its Countermeasures	UQ	SIGIR	2023	[PUB] [PDF]
FedAds: A Benchmark for Privacy-Preserving CVR Estimation with Vertical Federated Learning	Alibaba Group	SIGIR	2023	[PUB] [PDF] [CODE]
Edge-cloud Collaborative Learning with Federated and Centralized Features (short-paper)	ZJU	SIGIR	2023	[PUB] [PDF]
FLIRT: Federated Learning for Information Retrieval (extended-abstract)	IMT Lucca	SIGIR	2023	[PUB]
Is Non-IID Data a Threat in Federated Online Learning to Rank?	The University of Queensland	SIGIR	2022	[PUB] [CODE]
FedCT: Federated Collaborative Transfer for Recommendation	Rutgers University	SIGIR	2021	[PUB] [PDF] [CODE]
On the Privacy of Federated Pipelines	Technical University of Munich	SIGIR	2021	[PUB]
FedCMR: Federated Cross-Modal Retrieval.	Dalian University of Technology	SIGIR	2021	[PUB] [CODE]
Meta Matrix Factorization for Federated Rating Predictions.	SDU	SIGIR	2020	[PUB] [PDF]

fl in top db conference and journal

Federated Learning papers accepted by top Database conference and journal, including SIGMOD(ACM SIGMOD Conference) , ICDE(IEEE International Conference on Data Engineering) and VLDB(Very Large Data Bases Conference).

fl in top db conference and journal

Title	Affiliation	Venue	Year	Materials
Performance-Based Pricing of Federated Learning via Auction	Alibaba Group	VLDB	2024	[PUB] [CODE]
A Blockchain System for Clustered Federated Learning with Peer-to-Peer Knowledge Transfer	NJU	VLDB	2024	[PUB] [CODE]
Communication Efficient and Provable Federated Unlearning	SDU; KAUST	VLDB	2024	[PUB] [PDF] [CODE]
Enhancing Decentralized Federated Learning for Non-IID Data on Heterogeneous Devices	USTC	ICDE	2023	[PUB]
Dynamic Activation of Clients and Parameters for Federated Learning over Heterogeneous Graphs	Columbia University	ICDE	2023	[PUB] [CODE]
FedKNOW: Federated Continual Learning with Signature Task Knowledge Integration at Edge	BIT	ICDE	2023	[PUB] [PDF]
Lumos: Heterogeneity-aware Federated Graph Learning over Decentralized Devices	SJTU	ICDE	2023	[PUB] [PDF]
Federated IoT Interaction Vulnerability Analysis	MSU	ICDE	2023	[PUB]
Distribution-Regularized Federated Learning on Non-IID Data	BUAA	ICDE	2023	[PUB]
Fed-SC: One-Shot Federated Subspace Clustering over High-Dimensional Data	ShanghaiTech University	ICDE	2023	[PUB] [CODE]
FLBooster: A Unified and Efficient Platform for Federated Learning Acceleration	ZJU	ICDE	2023	[PUB]
FedGTA: Topology-aware Averaging for Federated Graph Learning.	BIT	VLDB	2023	[PUB] [CODE]
FS-Real: A Real-World Cross-Device Federated Learning Platform.	Alibaba Group	VLDB	2023	[PUB] [PDF] [CODE]
Federated Calibration and Evaluation of Binary Classifiers.	meta	VLDB	2023	[PUB] [PDF] [CODE]
Olive: Oblivious Federated Learning on Trusted Execution Environment Against the Risk of Sparsification.	Kyoto University	VLDB	2023	[PUB] [PDF] [CODE]
Falcon: A Privacy-Preserving and Interpretable Vertical Federated Learning System.	NUS	VLDB	2023	[PUB] [CODE]
Differentially Private Vertical Federated Clustering.	Purdue University	VLDB	2023	[PUB] [PDF] [CODE]
FederatedScope: A Flexible Federated Learning Platform for Heterogeneity.	Alibaba	VLDB	2023	[PUB] [PDF] [CODE]
Secure Shapley Value for Cross-Silo Federated Learning.	Kyoto University	VLDB	2023	[PUB] [PDF] [CODE]
OpBoost: A Vertical Federated Tree Boosting Framework Based on Order-Preserving Desensitization	ZJU	VLDB	2022	[PUB] [PDF] [CODE]
Skellam Mixture Mechanism: a Novel Approach to Federated Learning with Differential Privacy.	NUS	VLDB	2022	[PUB] [CODE]
Towards Communication-efficient Vertical Federated Learning Training via Cache-enabled Local Update	PKU	VLDB	2022	[PUB] [PDF] [CODE]
FedTSC: A Secure Federated Learning System for Interpretable Time Series Classification.	HIT	VLDB	2022	[PUB] [CODE]
Improving Fairness for Data Valuation in Horizontal Federated Learning	The UBC	ICDE	2022	[PUB] [PDF]
FedADMM: A Robust Federated Deep Learning Framework with Adaptivity to System Heterogeneity	USTC	ICDE	2022	[PUB] [PDF] [CODE]
FedMP: Federated Learning through Adaptive Model Pruning in Heterogeneous Edge Computing.	USTC	ICDE	2022	[PUB]
Federated Learning on Non-IID Data Silos: An Experimental Study.	NUS	ICDE	2022	[PUB] [PDF] [CODE]
Enhancing Federated Learning with Intelligent Model Migration in Heterogeneous Edge Computing	USTC	ICDE	2022	[PUB]
Samba: A System for Secure Federated Multi-Armed Bandits	Univ. Clermont Auvergne	ICDE	2022	[PUB] [CODE]
FedRecAttack: Model Poisoning Attack to Federated Recommendation	ZJU	ICDE	2022	[PUB] [PDF] [CODE]
Enhancing Federated Learning with In-Cloud Unlabeled Data	USTC	ICDE	2022	[PUB]
Efficient Participant Contribution Evaluation for Horizontal and Vertical Federated Learning	USTC	ICDE	2022	[PUB]
An Introduction to Federated Computation	University of Warwick; Facebook	SIGMOD Tutorial	2022	[PUB]
BlindFL: Vertical Federated Machine Learning without Peeking into Your Data	PKU; Tencent	SIGMOD	2022	[PUB] [PDF]
An Efficient Approach for Cross-Silo Federated Learning to Rank	BUAA	ICDE	2021	[PUB] [RELATED PAPER(ZH)]
Feature Inference Attack on Model Predictions in Vertical Federated Learning	NUS	ICDE	2021	[PUB] [PDF] [CODE]
Efficient Federated-Learning Model Debugging	USTC	ICDE	2021	[PUB]
Federated Matrix Factorization with Privacy Guarantee	Purdue	VLDB	2021	[PUB]
Projected Federated Averaging with Heterogeneous Differential Privacy.	Renmin University of China	VLDB	2021	[PUB] [CODE]
Enabling SQL-based Training Data Debugging for Federated Learning	Simon Fraser University	VLDB	2021	[PUB] [PDF] [CODE]
Refiner: A Reliable Incentive-Driven Federated Learning System Powered by Blockchain	ZJU	VLDB	2021	[PUB]
Tanium Reveal: A Federated Search Engine for Querying Unstructured File Data on Large Enterprise Networks	Tanium Inc.	VLDB	2021	[PUB] [VIDEO]
VF2Boost: Very Fast Vertical Federated Gradient Boosting for Cross-Enterprise Learning	PKU	SIGMOD	2021	[PUB]
ExDRa: Exploratory Data Science on Federated Raw Data	SIEMENS	SIGMOD	2021	[PUB]
Joint blockchain and federated learning-based offloading in harsh edge computing environments	TJU	SIGMOD workshop	2021	[PUB]
Privacy Preserving Vertical Federated Learning for Tree-based Models	NUS	VLDB	2020	[PUB] [PDF] [VIDEO] [CODE]

fl in top network conference and journal

Federated Learning papers accepted by top Database conference and journal, including SIGCOMM(Conference on Applications, Technologies, Architectures, and Protocols for Computer Communication), INFOCOM(IEEE Conference on Computer Communications), MobiCom(ACM/IEEE International Conference on Mobile Computing and Networking), NSDI(Symposium on Networked Systems Design and Implementation) and WWW(The Web Conference).

SIGCOMM NULL
INFOCOM 2023, 2022(Page), 2021(Page), 2020(Page), 2019, 2018
MobiCom 2023, 2022, 2021, 2020
NSDI 2023(Spring, Fall)
WWW 2023, 2022, 2021

fl in top network conference and journal

Title	Affiliation	Venue	Year	Materials
AutoFed: Heterogeneity-Aware Federated Multimodal Learning for Robust Autonomous Driving	NTU	MobiCom	2023	[PUB] [PDF]
Efficient Federated Learning for Modern NLP	Beiyou Shenzhen Institute	MobiCom	2023	[PDF] [解读]
FLASH: Towards a High-performance Hardware Acceleration Architecture for Cross-silo Federated Learning	HKUST; Clustar	NSDI	2023	[PUB] [SLIDE] [VIDEO]
To Store or Not? Online Data Selection for Federated Learning with Limited Storage.	SJTU	WWW	2023	[PUB] [PDF]
pFedPrompt: Learning Personalized Prompt for Vision-Language Models in Federated Learning.	PolyU	WWW	2023	[PUB]
Quantifying and Defending against Privacy Threats on Federated Knowledge Graph Embedding.	ZJU; HIC-ZJU	WWW	2023	[PUB] [PDF]
Vertical Federated Knowledge Transfer via Representation Distillation for Healthcare Collaboration Networks	PKU	WWW	2023	[PUB] [PDF] [CODE]
Semi-decentralized Federated Ego Graph Learning for Recommendation	SUST	WWW	2023	[PUB] [PDF]
FlexiFed: Personalized Federated Learning for Edge Clients with Heterogeneous Model Architectures.	Swinburne	WWW	2023	[PUB] [CODE]
FedEdge: Accelerating Edge-Assisted Federated Learning.	Swinburne	WWW	2023	[PUB]
Federated Node Classification over Graphs with Latent Link-type Heterogeneity.	Emory University	WWW	2023	[PUB] [CODE]
FedACK: Federated Adversarial Contrastive Knowledge Distillation for Cross-Lingual and Cross-Model Social Bot Detection.	USTC	WWW	2023	[PUB] [PDF] [CODE]
Interaction-level Membership Inference Attack Against Federated Recommender Systems.	UQ	WWW	2023	[PUB] [PDF]
AgrEvader: Poisoning Membership Inference against Byzantine-robust Federated Learning.	Deakin University	WWW	2023	[PUB]
Heterogeneous Federated Knowledge Graph Embedding Learning and Unlearning.	NJU	WWW	2023	[PUB] [PDF] [CODE]
Federated Learning for Metaverse: A Survey.	JNU	WWW (Companion Volume)	2023	[PUB] [PDF]
Understanding the Impact of Label Skewness and Optimization on Federated Learning for Text Classification	KU Leuven	WWW (Companion Volume)	2023	[PUB]
Privacy-Preserving Online Content Moderation: A Federated Learning Use Case.	CUT	WWW (Companion Volume)	2023	[PUB] [PDF]
Privacy-Preserving Online Content Moderation with Federated Learning.	CUT	WWW (Companion Volume)	2023	[PUB]
A Federated Learning Benchmark for Drug-Target Interaction.	University of Turin	WWW (Companion Volume)	2023	[PUB] [PDF] [CODE]
Towards a Decentralized Data Hub and Query System for Federated Dynamic Data Spaces.	TU Berlin	WWW (Companion Volume)	2023	[PUB]
1st Workshop on Federated Learning Technologies1st Workshop on Federated Learning Technologies	University of Turin	WWW (Companion Volume)	2023	[PUB]
A Survey of Trustworthy Federated Learning with Perspectives on Security, Robustness and Privacy	CUHK	WWW (Companion Volume)	2023	[PUB] [PDF]
A Hierarchical Knowledge Transfer Framework for Heterogeneous Federated Learning	THU	INFOCOM	2023	[PUB]
A Reinforcement Learning Approach for Minimizing Job Completion Time in Clustered Federated Learning	Southeast University	INFOCOM	2023	[PUB]
Adaptive Configuration for Heterogeneous Participants in Decentralized Federated Learning	USTC	INFOCOM	2023	[PUB] [PDF]
AnycostFL: Efficient On-Demand Federated Learning over Heterogeneous Edge Devices	Guangdong University of Technology	INFOCOM	2023	[PUB] [PDF]
AOCC-FL: Federated Learning with Aligned Overlapping via Calibrated Compensation	HUST	INFOCOM	2023	[PUB]
Asynchronous Federated Unlearning	University of Toronto	INFOCOM	2023	[PUB] [PDF] [CODE]
Communication-Efficient Federated Learning for Heterogeneous Edge Devices Based on Adaptive Gradient Quantization	PSU	INFOCOM	2023	[PUB] [PDF]
Enabling Communication-Efficient Federated Learning via Distributed Compressed Sensing	Beihang University	INFOCOM	2023	[PUB]
Federated Learning under Heterogeneous and Correlated Client Availability	Inria	INFOCOM	2023	[PUB] [PDF] [CODE]
Federated Learning with Flexible Control	IBM	INFOCOM	2023	[PUB] [PDF] [CODE]
Federated PCA on Grassmann Manifold for Anomaly Detection in IoT Networks	The University of Sydney	INFOCOM	2023	[PUB] [PDF]
FedMoS: Taming Client Drift in Federated Learning with Double Momentum and Adaptive Selection	HUST	INFOCOM	2023	[PUB] [PDF] [CODE]
FedSDG-FS: Efficient and Secure Feature Selection for Vertical Federated Learning	NTU	INFOCOM	2023	[PUB] [PDF]
Heterogeneity-Aware Federated Learning with Adaptive Client Selection and Gradient Compression	USTC	INFOCOM	2023
Joint Edge Aggregation and Association for Cost-Efficient Multi-Cell Federated Learning	NUDT	INFOCOM	2023	[PUB]
Joint Participation Incentive and Network Pricing Design for Federated Learning	Northwestern University	INFOCOM	2023	[PUB]
More than Enough is Too Much: Adaptive Defenses against Gradient Leakage in Production Federated Learning	University of Toronto	INFOCOM	2023	[PUB] [PDF] [WEIBO]
Network Adaptive Federated Learning: Congestion and Lossy Compression	UTAustin	INFOCOM	2023	[PUB] [PDF]
OBLIVION: Poisoning Federated Learning by Inducing Catastrophic Forgetting	The Hang Seng University of Hong Kong	INFOCOM	2023	[PUB] [CODE]
Privacy as a Resource in Differentially Private Federated Learning	BUPT	INFOCOM	2023	[PUB]
SplitGP: Achieving Both Generalization and Personalization in Federated Learning	KAIST	INFOCOM	2023	[PUB] [PDF]
SVDFed: Enabling Communication-Efficient Federated Learning via Singular-Value-Decomposition	Beihang University	INFOCOM	2023	[PUB]
Tackling System Induced Bias in Federated Learning: Stratification and Convergence Analysis	Southern University of Science and Technology	INFOCOM	2023	[PUB] [PDF]
Toward Sustainable AI: Federated Learning Demand Response in Cloud-Edge Systems via Auctions	BUPT	INFOCOM	2023	[PUB] [PDF]
Truthful Incentive Mechanism for Federated Learning with Crowdsourced Data Labeling	Auburn University	INFOCOM	2023	[PUB] [PDF]
TVFL: Tunable Vertical Federated Learning towards Communication-Efficient Model Serving	USTC	INFOCOM	2023	[PUB]
PyramidFL: Fine-grained Data and System Heterogeneity-aware Client Selection for Efficient Federated Learning	MSU	MobiCom	2022	[PUB] [PDF] [CODE]
NestFL: efficient federated learning through progressive model pruning in heterogeneous edge computing	pmlabs	MobiCom(Poster)	2022	[PUB]
Federated learning-based air quality prediction for smart cities using BGRU model	IITM	MobiCom(Poster)	2022	[PUB]
FedHD: federated learning with hyperdimensional computing	UCSD	MobiCom(Demo)	2022	[PUB] [CODE]
Joint Superposition Coding and Training for Federated Learning over Multi-Width Neural Networks	Korea University	INFOCOM	2022	[PUB]
Towards Optimal Multi-Modal Federated Learning on Non-IID Data with Hierarchical Gradient Blending	University of Toronto	INFOCOM	2022	[PUB]
Optimal Rate Adaption in Federated Learning with Compressed Communications	SZU	INFOCOM	2022	[PUB] [PDF]
The Right to be Forgotten in Federated Learning: An Efficient Realization with Rapid Retraining.	CityU	INFOCOM	2022	[PUB] [PDF]
Tackling System and Statistical Heterogeneity for Federated Learning with Adaptive Client Sampling.	CUHK; AIRS ;Yale University	INFOCOM	2022	[PUB] [PDF]
Communication-Efficient Device Scheduling for Federated Learning Using Stochastic Optimization	Army Research Laboratory, Adelphi	INFOCOM	2022	[PUB] [PDF]
FLASH: Federated Learning for Automated Selection of High-band mmWave Sectors	NEU	INFOCOM	2022	[PUB] [CODE]
A Profit-Maximizing Model Marketplace with Differentially Private Federated Learning	CUHK; AIRS	INFOCOM	2022	[PUB]
Protect Privacy from Gradient Leakage Attack in Federated Learning	PolyU	INFOCOM	2022	[PUB] [SLIDE]
FedFPM: A Unified Federated Analytics Framework for Collaborative Frequent Pattern Mining.	SJTU	INFOCOM	2022	[PUB] [CODE]
An Accuracy-Lossless Perturbation Method for Defending Privacy Attacks in Federated Learning	SWJTU;THU	WWW	2022	[PUB] [PDF] [CODE]
LocFedMix-SL: Localize, Federate, and Mix for Improved Scalability, Convergence, and Latency in Split Learning	Yonsei University	WWW	2022	[PUB]
Federated Unlearning via Class-Discriminative Pruning	PolyU	WWW	2022	[PUB] [PDF] [CODE]
FedKC: Federated Knowledge Composition for Multilingual Natural Language Understanding	Purdue	WWW	2022	[PUB]
Powering Multi-Task Federated Learning with Competitive GPU Resource Sharing.		WWW (Companion Volume)	2022
Federated Bandit: A Gossiping Approach	University of California	SIGMETRICS	2021	[PUB] [PDF]
Hermes: an efficient federated learning framework for heterogeneous mobile clients	Duke University	MobiCom	2021	[PUB]
Federated mobile sensing for activity recognition	Samsung AI Center	MobiCom	2021	[PUB] [PAGE] [TALKS] [VIDEO]
Learning for Learning: Predictive Online Control of Federated Learning with Edge Provisioning.	Nanjing University	INFOCOM	2021	[PUB]
Device Sampling for Heterogeneous Federated Learning: Theory, Algorithms, and Implementation.	Purdue	INFOCOM	2021	[PUB] [PDF]
FAIR: Quality-Aware Federated Learning with Precise User Incentive and Model Aggregation	THU	INFOCOM	2021	[PUB]
Sample-level Data Selection for Federated Learning	USTC	INFOCOM	2021	[PUB]
To Talk or to Work: Flexible Communication Compression for Energy Efficient Federated Learning over Heterogeneous Mobile Edge Devices	Xidian University; CAS	INFOCOM	2021	[PUB] [PDF]
Cost-Effective Federated Learning Design	CUHK; AIRS; Yale University	INFOCOM	2021	[PUB] [PDF]
An Incentive Mechanism for Cross-Silo Federated Learning: A Public Goods Perspective	The UBC	INFOCOM	2021	[PUB]
Resource-Efficient Federated Learning with Hierarchical Aggregation in Edge Computing	USTC	INFOCOM	2021	[PUB]
FedServing: A Federated Prediction Serving Framework Based on Incentive Mechanism.	Jinan University; CityU	INFOCOM	2021	[PUB] [PDF]
Federated Learning over Wireless Networks: A Band-limited Coordinated Descent Approach	Arizona State University	INFOCOM	2021	[PUB] [PDF]
Dual Attention-Based Federated Learning for Wireless Traffic Prediction	King Abdullah University of Science and Technology	INFOCOM	2021	[PUB] [PDF] [CODE]
FedSens: A Federated Learning Approach for Smart Health Sensing with Class Imbalance in Resource Constrained Edge Computing	University of Notre Dame	INFOCOM	2021	[PUB]
P-FedAvg: Parallelizing Federated Learning with Theoretical Guarantees	SYSU; Guangdong Key Laboratory of Big Data Analysis and Processing	INFOCOM	2021	[PUB]
Meta-HAR: Federated Representation Learning for Human Activity Recognition.	University of Alberta	WWW	2021	[PUB] [PDF] [CODE]
PFA: Privacy-preserving Federated Adaptation for Effective Model Personalization	PKU	WWW	2021	[PUB] [PDF] [CODE]
Communication Efficient Federated Generalized Tensor Factorization for Collaborative Health Data Analytics	Emory	WWW	2021	[PUB] [CODE]
Hierarchical Personalized Federated Learning for User Modeling	USTC	WWW	2021	[PUB]
Characterizing Impacts of Heterogeneity in Federated Learning upon Large-Scale Smartphone Data	PKU	WWW	2021	[PUB] [PDF] [SLIDE] [CODE]
Incentive Mechanism for Horizontal Federated Learning Based on Reputation and Reverse Auction	SYSU	WWW	2021	[PUB]
Physical-Layer Arithmetic for Federated Learning in Uplink MU-MIMO Enabled Wireless Networks.	Nanjing University	INFOCOM	2020	[PUB]
Optimizing Federated Learning on Non-IID Data with Reinforcement Learning	University of Toronto	INFOCOM	2020	[PUB] [SLIDE] [CODE] [解读]
Enabling Execution Assurance of Federated Learning at Untrusted Participants	THU	INFOCOM	2020	[PUB] [CODE]
Billion-scale federated learning on mobile clients: a submodel design with tunable privacy	SJTU	MobiCom	2020	[PUB]
Federated Learning over Wireless Networks: Optimization Model Design and Analysis	The University of Sydney	INFOCOM	2019	[PUB] [CODE]
Beyond Inferring Class Representatives: User-Level Privacy Leakage From Federated Learning	Wuhan University	INFOCOM	2019	[PUB] [PDF] [UC.]
InPrivate Digging: Enabling Tree-based Distributed Data Mining with Differential Privacy	Collaborative Innovation Center of Geospatial Technology	INFOCOM	2018	[PUB]

fl in top system conference and journal

Federated Learning papers accepted by top Database conference and journal, including OSDI(USENIX Symposium on Operating Systems Design and Implementation), SOSP(Symposium on Operating Systems Principles), ISCA(International Symposium on Computer Architecture), MLSys(Conference on Machine Learning and Systems), EuroSys(European Conference on Computer Systems), TPDS(IEEE Transactions on Parallel and Distributed Systems), DAC(Design Automation Conference), TOCS(ACM Transactions on Computer Systems), TOS(ACM Transactions on Storage), TCAD(IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems), TC(IEEE Transactions on Computers).

OSDI 2021
SOSP 2021
ISCA NULL
MLSys 2023, 2022, 2020, 2019
EuroSys 2023, 2022, 2021, 2020
TPDS 2023, 2022, 2021, 2020
DAC 2022, 2021
TOCS NULL
TOS NULL
TCAD 2023, 2022, 2021
TC 2023, 2022, 2021

fl in top system conference and journal

Title	Affiliation	Venue	Year	Materials
Collaboration in Federated Learning With Differential Privacy: A Stackelberg Game Analysis	SYSU	TPDS	2024	[PUB]
FAST: Enhancing Federated Learning Through Adaptive Data Sampling and Local Training	USTC	TPDS	2024	[PUB]
EcoFed: Efficient Communication for DNN Partitioning-Based Federated Learning	University of St Andrews	TPDS	2024	[PUB] [PDF] [CODE]
FedHAP: Federated Hashing With Global Prototypes for Cross-Silo Retrieval	THU	TPDS	2024	[PUB] [PDF]
FedComp: A Federated Learning Compression Framework for Resource-Constrained Edge Computing Devices	HIT	TCAD	2024	[PUB]
User-Distribution-Aware Federated Learning for Efficient Communication and Fast Inference	ECNU; SHU	TC	2024	[PUB]
FedRFQ: Prototype-Based Federated Learning With Reduced Redundancy, Minimal Failure, and Enhanced Quality	SDU	TC	2024	[PUB] [PDF]
Value of Information: A Comprehensive Metric for Client Selection in Federated Edge Learning	SDU	TC	2024	[PUB]
Age-Aware Data Selection and Aggregator Placement for Timely Federated Continual Learning in Mobile Edge Computing	DLUT	TC	2024	[PUB]
FedGKD: Toward Heterogeneous Federated Learning via Global Knowledge Distillation	HUST	TC	2024	[PUB] [PDF]
Digital Twin-Assisted Federated Learning Service Provisioning Over Mobile Edge Networks	SDU	TC	2024	[PUB]
REFL: Resource-Efficient Federated Learning	QMUL	EuroSys	2023	[PUB] [PDF] [CODE]
A First Look at the Impact of Distillation Hyper-Parameters in Federated Knowledge Distillation		EuroSys workshop	2023	[PUB]
Towards Practical Few-shot Federated NLP		EuroSys workshop	2023	[PUB]
Can Fair Federated Learning Reduce the need for Personalisation?		EuroSys workshop	2023	[PUB]
Gradient-less Federated Gradient Boosting Tree with Learnable Learning Rates		EuroSys workshop	2023	[PUB]
Towards Robust and Bias-free Federated Learning		EuroSys workshop	2023	[PUB]
FedTree: A Federated Learning System For Trees	UC Berkeley	MLSys	2023	[PUB] [CODE]
FLINT: A Platform for Federated Learning Integration	LinkedIn	MLSys	2023	[PUB] [PDF]
On Noisy Evaluation in Federated Hyperparameter Tuning	CMU	MLSys	2023	[PUB] [PDF] [CODE]
GlueFL: Reconciling Client Sampling and Model Masking for Bandwidth Efficient Federated Learning	UBC	MLSys	2023	[PUB] [PDF] [CODE]
Self-Supervised On-Device Federated Learning From Unlabeled Streams.	FDU	TCAD	2023	[PUB] [PDF]
Optimizing Training Efficiency and Cost of Hierarchical Federated Learning in Heterogeneous Mobile-Edge Cloud Computing	ECNU	TCAD	2023	[PUB]
Lightweight Blockchain-Empowered Secure and Efficient Federated Edge Learning	University of Exeter	TC	2023	[PUB]
Towards Data-Independent Knowledge Transfer in Model-Heterogeneous Federated Learning	PolyU	TC	2023	[PUB]
A New Federated Scheduling Algorithm for Arbitrary-Deadline DAG Tasks	NEFU	TC	2023	[PUB]
Privacy-Enhanced Decentralized Federated Learning at Dynamic Edge	SDU	TC	2023	[PUB]
Byzantine-Resilient Federated Learning at Edge	SDU	TC	2023	[PUB] [PDF]
PrivAim: A Dual-Privacy Preserving and Quality-Aware Incentive Mechanism for Federated Learning	CSU	TC	2023	[PUB]
Accelerating Federated Learning With a Global Biased Optimiser	University of Exeter	TC	2023	[PUB] [PDF] [CODE]
Type-Aware Federated Scheduling for Typed DAG Tasks on Heterogeneous Multicore Platforms	TU Dortmund University	TC	2023	[PUB] [CODE]
Sandbox Computing: A Data Privacy Trusted Sharing Paradigm Via Blockchain and Federated Learning.	BUPT	TC	2023	[PUB]
CHEESE: Distributed Clustering-Based Hybrid Federated Split Learning Over Edge Networks	SUDA	TPDS	2023	[PUB]
Hierarchical Federated Learning With Momentum Acceleration in Multi-Tier Networks	University of Sydney	TPDS	2023	[PUB] [PDF]
Dap-FL: Federated Learning Flourishes by Adaptive Tuning and Secure Aggregation	Xidian University	TPDS	2023	[PUB] [PDF] [CODE]
Collaborative Intrusion Detection System for SDVN: A Fairness Federated Deep Learning Approach	Anhui University	TPDS	2023	[PUB]
Energy-Aware, Device-to-Device Assisted Federated Learning in Edge Computing	ANU	TPDS	2023	[PUB]
Faster Federated Learning With Decaying Number of Local SGD Steps	University of Exeter	TPDS	2023	[PUB] [PDF] [CODE]
DRFL: Federated Learning in Diabetic Retinopathy Grading Using Fundus Images	National Institute of Technology Silchar	TPDS	2023	[PUB]
FedProf: Selective Federated Learning Based on Distributional Representation Profiling	Peng Cheng Laboratory	TPDS	2023	[PUB] [PDF] [UC]
Federated Ensemble Model-Based Reinforcement Learning in Edge Computing	University of Exeter	TPDS	2023	[PUB] [PDF]
Incentive Mechanism Design for Joint Resource Allocation in Blockchain-Based Federated Learning.	IUPUI	TPDS	2023	[PUB] [PDF]
HiFlash: Communication-Efficient Hierarchical Federated Learning With Adaptive Staleness Control and Heterogeneity-Aware Client-Edge Association.	SYSU	TPDS	2023	[PUB] [PDF]
From Deterioration to Acceleration: A Calibration Approach to Rehabilitating Step Asynchronism in Federated Optimization.	PolyU	TPDS	2023	[PUB] [PDF] [CODE]
Federated Learning Over Coupled Graphs	XJTU	TPDS	2023	[PUB] [PDF]
Privacy vs. Efficiency: Achieving Both Through Adaptive Hierarchical Federated Learning	NUDT	TPDS	2023	[PUB]
On Model Transmission Strategies in Federated Learning With Lossy Communications	SZU	TPDS	2023	[PUB]
Scheduling Algorithms for Federated Learning With Minimal Energy Consumption	University of Bordeaux	TPDS	2023	[PUB] [PDF] [CODE]
Auction-Based Cluster Federated Learning in Mobile Edge Computing Systems	HIT	TPDS	2023	[PUB] [PDF]
Personalized Edge Intelligence via Federated Self-Knowledge Distillation.	HUST	TPDS	2023	[PUB] [CODE]
Design of a Quantization-Based DNN Delta Compression Framework for Model Snapshots and Federated Learning.	HIT	TPDS	2023	[PUB]
Multi-Job Intelligent Scheduling With Cross-Device Federated Learning.	Baidu	TPDS	2023	[PUB] [PDF]
Data-Centric Client Selection for Federated Learning Over Distributed Edge Networks.	IIT	TPDS	2023	[PUB]
GossipFL: A Decentralized Federated Learning Framework With Sparsified and Adaptive Communication.	HKBU	TPDS	2023	[PUB]
FedMDS: An Efficient Model Discrepancy-Aware Semi-Asynchronous Clustered Federated Learning Framework.	CQU	TPDS	2023	[PUB]
HierFedML: Aggregator Placement and UE Assignment for Hierarchical Federated Learning in Mobile Edge Computing.	DUT	TPDS	2023	[PUB]
Data selection for efficient model update in federated learning		EuroSys workshop	2022	[PUB]
Empirical analysis of federated learning in heterogeneous environments		EuroSys workshop	2022	[PUB]
BAFL: A Blockchain-Based Asynchronous Federated Learning Framework		TC	2022	[PUB] [CODE]
L4L: Experience-Driven Computational Resource Control in Federated Learning		TC	2022	[PUB]
Adaptive Federated Learning on Non-IID Data With Resource Constraint		TC	2022	[PUB]
Locking Protocols for Parallel Real-Time Tasks With Semaphores Under Federated Scheduling.		TCAD	2022	[PUB]
Client Scheduling and Resource Management for Efficient Training in Heterogeneous IoT-Edge Federated Learning	ECNU	TCAD	2022	[PUB]
PervasiveFL: Pervasive Federated Learning for Heterogeneous IoT Systems.	ECNU	TCAD	2022	[PUB]
FHDnn: communication efficient and robust federated learning for AIoT networks	UC San Diego	DAC	2022	[PUB]
A Decentralized Federated Learning Framework via Committee Mechanism With Convergence Guarantee	SYSU	TPDS	2022	[PUB] [PDF]
Improving Federated Learning With Quality-Aware User Incentive and Auto-Weighted Model Aggregation	THU	TPDS	2022	[PUB]
$f$funcX: Federated Function as a Service for Science.	SUST	TPDS	2022	[PUB] [PDF]
Blockchain Assisted Decentralized Federated Learning (BLADE-FL): Performance Analysis and Resource Allocation	NUST	TPDS	2022	[PUB] [PDF] [CODE]
Adaptive Federated Deep Reinforcement Learning for Proactive Content Caching in Edge Computing.	CQU	TPDS	2022	[PUB]
TDFL: Truth Discovery Based Byzantine Robust Federated Learning	BIT	TPDS	2022	[PUB]
Federated Learning With Nesterov Accelerated Gradient	The University of Sydney	TPDS	2022	[PUB] [PDF]
FedGraph: Federated Graph Learning with Intelligent Sampling	UoA	TPDS	2022	[PUB] [CODE] [解读]
AUCTION: Automated and Quality-Aware Client Selection Framework for Efficient Federated Learning.	THU	TPDS	2022	[PUB]
DONE: Distributed Approximate Newton-type Method for Federated Edge Learning.	University of Sydney	TPDS	2022	[PUB] [PDF] [CODE]
Flexible Clustered Federated Learning for Client-Level Data Distribution Shift.	CQU	TPDS	2022	[PUB] [PDF] [CODE]
Min-Max Cost Optimization for Efficient Hierarchical Federated Learning in Wireless Edge Networks.	Xidian University	TPDS	2022	[PUB]
LightFed: An Efficient and Secure Federated Edge Learning System on Model Splitting.	CSU	TPDS	2022	[PUB]
On the Benefits of Multiple Gossip Steps in Communication-Constrained Decentralized Federated Learning.	Purdue	TPDS	2022	[PUB] [PDF] [CODE]
Incentive-Aware Autonomous Client Participation in Federated Learning.	Sun Yat-sen University	TPDS	2022	[PUB]
Communicational and Computational Efficient Federated Domain Adaptation.	HKUST	TPDS	2022	[PUB]
Decentralized Edge Intelligence: A Dynamic Resource Allocation Framework for Hierarchical Federated Learning.	NTU	TPDS	2022	[PUB]
Differentially Private Byzantine-Robust Federated Learning.	Qufu Normal University	TPDS	2022	[PUB]
Multi-Task Federated Learning for Personalised Deep Neural Networks in Edge Computing.	University of Exeter	TPDS	2022	[PUB] [PDF] [CODE]
Reputation-Aware Hedonic Coalition Formation for Efficient Serverless Hierarchical Federated Learning.	BUAA	TPDS	2022	[PUB]
Differentially Private Federated Temporal Difference Learning.	Stony Brook University	TPDS	2022	[PUB]
Towards Efficient and Stable K-Asynchronous Federated Learning With Unbounded Stale Gradients on Non-IID Data.	XJTU	TPDS	2022	[PUB] [PDF]
Communication-Efficient Federated Learning With Compensated Overlap-FedAvg.	SCU	TPDS	2022	[PUB] [PDF] [CODE]
PAPAYA: Practical, Private, and Scalable Federated Learning.	Meta AI	MLSys	2022	[PUB] [PDF]
LightSecAgg: a Lightweight and Versatile Design for Secure Aggregation in Federated Learning	USC	MLSys	2022	[PUB] [PDF] [CODE]
Accelerated Training via Device Similarity in Federated Learning		EuroSys workshop	2021	[PUB]
Towards Federated Learning with Attention Transfer to Mitigate System and Data Heterogeneity of Clients		EuroSys workshop	2021	[PUB]
Towards Mitigating Device Heterogeneity in Federated Learning via Adaptive Model Quantization		EuroSys workshop	2021	[PUB]
SAFA: A Semi-Asynchronous Protocol for Fast Federated Learning With Low Overhead	University of Warwick	TC	2021	[PDF] [PUB] [CODE]
Efficient Federated Learning for Cloud-Based AIoT Applications	ECNU	TCAD	2021	[PUB]
HADFL: Heterogeneity-aware Decentralized Federated Learning Framework	USTC	DAC	2021	[PDF] [PUB]
Helios: Heterogeneity-Aware Federated Learning with Dynamically Balanced Collaboration.	GMU	DAC	2021	[PDF] [PUB]
FedLight: Federated Reinforcement Learning for Autonomous Multi-Intersection Traffic Signal Control.	ECNU	DAC	2021	[PUB]
Oort: Efficient Federated Learning via Guided Participant Selection	University of Michigan	OSDI	2021	[PUB] [PDF] [CODE] [SLIDES] [VIDEO]
Towards Efficient Scheduling of Federated Mobile Devices Under Computational and Statistical Heterogeneity.	Old Dominion University	TPDS	2021	[PUB] [PDF]
Self-Balancing Federated Learning With Global Imbalanced Data in Mobile Systems.	CQU	TPDS	2021	[PUB] [CODE]
An Efficiency-Boosting Client Selection Scheme for Federated Learning With Fairness Guarantee	SCUT	TPDS	2021	[PUB] [PDF] [解读]
Proof of Federated Learning: A Novel Energy-Recycling Consensus Algorithm.	Beijing Normal University	TPDS	2021	[PUB] [PDF]
Biscotti: A Blockchain System for Private and Secure Federated Learning.	UBC	TPDS	2021	[PUB]
Mutual Information Driven Federated Learning.	Deakin University	TPDS	2021	[PUB]
Accelerating Federated Learning Over Reliability-Agnostic Clients in Mobile Edge Computing Systems.	University of Warwick	TPDS	2021	[PUB] [PDF]
FedSCR: Structure-Based Communication Reduction for Federated Learning.	HKU	TPDS	2021	[PUB]
FedScale: Benchmarking Model and System Performance of Federated Learning	University of Michigan	SOSP workshop / ICML 2022	2021	[PUB] [PDF] [CODE] [解读]
Redundancy in cost functions for Byzantine fault-tolerant federated learning		SOSP workshop	2021	[PUB]
Towards an Efficient System for Differentially-private, Cross-device Federated Learning		SOSP workshop	2021	[PUB]
GradSec: a TEE-based Scheme Against Federated Learning Inference Attacks		SOSP workshop	2021	[PUB]
Community-Structured Decentralized Learning for Resilient EI.		SOSP workshop	2021	[PUB]
Separation of Powers in Federated Learning (Poster Paper)	IBM Research	SOSP workshop	2021	[PUB] [PDF]
Towards federated unsupervised representation learning		EuroSys workshop	2020	[PUB]
CoLearn: enabling federated learning in MUD-compliant IoT edge networks		EuroSys workshop	2020	[PUB]
LDP-Fed: federated learning with local differential privacy.		EuroSys workshop	2020	[PUB]
Accelerating Federated Learning via Momentum Gradient Descent.	USTC	TPDS	2020	[PUB] [PDF]
Towards Fair and Privacy-Preserving Federated Deep Models.	NUS	TPDS	2020	[PUB] [PDF] [CODE]
Federated Optimization in Heterogeneous Networks	CMU	MLSys	2020	[PUB] [PDF] [CODE]
Towards Federated Learning at Scale: System Design	Google	MLSys	2019	[PUB] [PDF] [解读]

fl in top conference and journal other fields

Federated Learning papers accepted by top conference and journal in the other fields, including ICSE(International Conference on Software Engineering), FOCS(IEEE Annual Symposium on Foundations of Computer Science), STOC(Symposium on the Theory of Computing).

ICSE 2023, 2021
FOCS Null
STOC Null

fl in top conference and journal other fields

Title	Affiliation	Venue	Year	Materials
FedDebug: Systematic Debugging for Federated Learning Applications.	Virginia Tech	ICSE	2023	pub pdf code
FedSlice: Protecting Federated Learning Models from Malicious Participants with Model Slicing.	PKU	ICSE	2023	pub code
Towards a Self-Adaptive Architecture for Federated Learning of Industrial Automation Systems		SEAMS@ICSE workshop	2021	pub
Federated Machine Learning as a Self-Adaptive Problem		SEAMS@ICSE workshop	2021	pub

fl on graph data and graph neural networks

This section partially refers to DBLP search engine and repositories Awesome-Federated-Learning-on-Graph-and-GNN-papers and Awesome-Federated-Machine-Learning.

fl on graph data and graph neural networks

Title	Affiliation	Venue	Year	Materials
FedGCN: Convergence and Communication Tradeoffs in Federated Training of Graph Convolutional Networks	CMU	NeurIPS	2023	[PDF] [CODE]
Wyze Rule: Federated Rule Dataset for Rule Recommendation Benchmarking	CMU	NeurIPS Dataset Track	2023	[PDF] [DATASET] [CODE]
Federated Visualization: A Privacy-Preserving Strategy for Aggregated Visual Query.	ZJU	IEEE Trans. Vis. Comput. Graph.	2023	[PUB] [PDF]
Personalized Subgraph Federated Learning	KAIST	ICML	2023	[PDF]
Semi-decentralized Federated Ego Graph Learning for Recommendation	SUST	WWW	2023	[PUB] [PDF]
Federated Graph Neural Network for Fast Anomaly Detection in Controller Area Networks	ECUST	IEEE Trans. Inf. Forensics Secur.	2023	[PUB]
Federated Learning Over Coupled Graphs	XJTU	IEEE Trans. Parallel Distributed Syst.	2023	[PUB] [PDF]
HetVis: A Visual Analysis Approach for Identifying Data Heterogeneity in Horizontal Federated Learning	Nankai University	IEEE Trans. Vis. Comput. Graph.	2023	[PUB] [PDF]
Federated Learning on Non-IID Graphs via Structural Knowledge Sharing	UTS	AAAI	2023	[PDF] [CODE]
FedGS: Federated Graph-based Sampling with Arbitrary Client Availability	XMU	AAAI	2023	[PDF] [CODE]
An Information Theoretic Perspective for Heterogeneous Subgraph Federated Learning.	PKU	DASFAA	2023	[PUB]
GraphCS: Graph-based client selection for heterogeneity in federated learning	NUDT	J. Parallel Distributed Comput.	2023	[PUB]
Towards On-Device Federated Learning: A Direct Acyclic Graph-based Blockchain Approach	BUPT	IEEE Trans. Neural Networks Learn. Syst.	2023	[PUB] [PDF]
Short-Term Traffic Flow Prediction Based on Graph Convolutional Networks and Federated Learning	ZUEL	IEEE Trans. Intell. Transp. Syst.	2023	[PUB]
Hyper-Graph Attention Based Federated Learning Methods for Use in Mental Health Detection.	HVL	IEEE J. Biomed. Health Informatics	2023	[PUB]
Federated Learning-Based Cross-Enterprise Recommendation With Graph Neural		IEEE Trans. Ind. Informatics	2023	[PUB]
Graph-Fraudster: Adversarial Attacks on Graph Neural Network Based Vertical Federated Learning	ZJUT	IEEE Trans. Comput. Soc. Syst.	2023	[PUB] [PDF] [CODE]
ESA-FedGNN: Efficient secure aggregation for federated graph neural networks.		Peer Peer Netw. Appl.	2023	[PUB]
FedCKE: Cross-Domain Knowledge Graph Embedding in Federated Learning	SWJTU	IEEE Trans. Big Data	2023	[PUB]
Asynchronous federated learning with directed acyclic graph-based blockchain in edge computing: Overview, design, and challenges.		Expert Syst. Appl.	2023	[PUB]
FedGR: Federated Graph Neural Network for Recommendation System	CUPT	Axioms	2023	[PUB]
S-Glint: Secure Federated Graph Learning With Traffic Throttling and Flow Scheduling.		IEEE Trans. Green Commun. Netw.	2023	[PUB]
FedAGCN: A traffic flow prediction framework based on federated learning and Asynchronous Graph Convolutional Network		Appl. Soft Comput.	2023	[PUB]
GDFed: Dynamic Federated Learning for Heterogenous Device Using Graph Neural Network	KHU	ICOIN	2023	[PUB] [CODE]
Coordinated Scheduling and Decentralized Federated Learning Using Conflict Clustering Graphs in Fog-Assisted IoD Networks	UBC	IEEE Trans. Veh. Technol.	2023	[PUB]
FedRule: Federated Rule Recommendation System with Graph Neural Networks	CMU	IoTDI	2023	[PUB] [PDF] [CODE]
FedWalk: Communication Efficient Federated Unsupervised Node Embedding with Differential Privacy	SJTU	KDD	2022	[PUB] [PDF]
FederatedScope-GNN: Towards a Unified, Comprehensive and Efficient Platform for Federated Graph Learning	Alibaba	KDD (Best Paper Award)	2022	[PDF] [CODE] [PUB]
Deep Neural Network Fusion via Graph Matching with Applications to Model Ensemble and Federated Learning	SJTU	ICML	2022	[PUB] [CODE]
Meta-Learning Based Knowledge Extrapolation for Knowledge Graphs in the Federated Setting `kg.`	ZJU	IJCAI	2022	[PUB] [PDF] [CODE]
Personalized Federated Learning With a Graph	UTS	IJCAI	2022	[PUB] [PDF] [CODE]
Vertically Federated Graph Neural Network for Privacy-Preserving Node Classification	ZJU	IJCAI	2022	[PUB] [PDF]
SpreadGNN: Decentralized Multi-Task Federated Learning for Graph Neural Networks on Molecular Data	USC	AAAI	2022	[PUB] [PDF] [CODE] [解读]
FedGraph: Federated Graph Learning with Intelligent Sampling	UoA	TPDS	2022	[PUB] [CODE] [解读]
Federated Graph Machine Learning: A Survey of Concepts, Techniques, and Applications `surv.`	University of Virginia	SIGKDD Explor.	2022	[PUB] [PDF]
Semantic Vectorization: Text- and Graph-Based Models.	IBM Research	Federated Learning	2022	[PUB]
GraphFL: A Federated Learning Framework for Semi-Supervised Node Classification on Graphs	IIT	ICDM	2022	[PUB] [PDF] [解读]
More is Better (Mostly): On the Backdoor Attacks in Federated Graph Neural Networks	TU Delft	ACSAC	2022	[PUB] [PDF]
FedNI: Federated Graph Learning with Network Inpainting for Population-Based Disease Prediction	UESTC	TMI	2022	[PUB] [PDF]
SemiGraphFL: Semi-supervised Graph Federated Learning for Graph Classification.	PKU	PPSN	2022	[PUB]
Federated Spatio-Temporal Traffic Flow Prediction Based on Graph Convolutional Network	TJU	WCSP	2022	[PUB]
A federated graph neural network framework for privacy-preserving personalization	THU	Nature Communications	2022	[PUB] [CODE] [解读]
Malicious Transaction Identification in Digital Currency via Federated Graph Deep Learning	BIT	INFOCOM Workshops	2022	[PUB]
Efficient Federated Learning on Knowledge Graphs via Privacy-preserving Relation Embedding Aggregation `kg.`	Lehigh University	EMNLP	2022	[PUB] [PDF] [CODE]
Power Allocation for Wireless Federated Learning using Graph Neural Networks	Rice University	ICASSP	2022	[PUB] [PDF] [CODE]
Privacy-Preserving Federated Multi-Task Linear Regression: A One-Shot Linear Mixing Approach Inspired By Graph Regularization	UC	ICASSP	2022	[PUB] [PDF] [CODE]
Graph-regularized federated learning with shareable side information	NWPU	Knowl. Based Syst.	2022	[PUB]
Federated knowledge graph completion via embedding-contrastive learning `kg.`	ZJU	Knowl. Based Syst.	2022	[PUB]
Federated Graph Learning with Periodic Neighbour Sampling	HKU	IWQoS	2022	[PUB]
FedGSL: Federated Graph Structure Learning for Local Subgraph Augmentation.		Big Data	2022	[PUB]
Domain-Aware Federated Social Bot Detection with Multi-Relational Graph Neural Networks.	UCAS; CAS	IJCNN	2022	[PUB]
A Federated Multi-Server Knowledge Graph Embedding Framework For Link Prediction.		ICTAI	2022	[PUB]
A Privacy-Preserving Subgraph-Level Federated Graph Neural Network via Differential Privacy	Ping An Technology	KSEM	2022	[PUB] [PDF]
Clustered Graph Federated Personalized Learning.	NTNU	IEEECONF	2022	[PUB]
Investigating the Predictive Reproducibility of Federated Graph Neural Networks using Medical Datasets.		MICCAI Workshop	2022	[PDF] [CODE]
Peer-to-Peer Variational Federated Learning Over Arbitrary Graphs	UCSD	Int. J. Bio Inspired Comput.	2022	[PUB]
Federated Multi-task Graph Learning	ZJU	ACM Trans. Intell. Syst. Technol.	2022	[PUB]
Graph-Based Traffic Forecasting via Communication-Efficient Federated Learning	SUSTech	WCNC	2022	[PUB]
Federated meta-learning for spatial-temporal prediction	NEU	Neural Comput. Appl.	2022	[PUB] [CODE]
BiG-Fed: Bilevel Optimization Enhanced Graph-Aided Federated Learning	NTU	IEEE Transactions on Big Data	2022	[PUB] [PDF]
Leveraging Spanning Tree to Detect Colluding Attackers in Federated Learning	Missouri S&T	INFCOM Workshops	2022	[PUB]
Federated learning of molecular properties with graph neural networks in a heterogeneous setting	University of Rochester	Patterns	2022	[PUB] [PDF] [CODE]
Graph Federated Learning for CIoT Devices in Smart Home Applications	University of Toronto	IEEE Internet Things J.	2022	[PUB] [PDF] [CODE]
Multi-Level Federated Graph Learning and Self-Attention Based Personalized Wi-Fi Indoor Fingerprint Localization	SYSU	IEEE Commun. Lett.	2022	[PUB]
Graph-Assisted Communication-Efficient Ensemble Federated Learning	UC	EUSIPCO	2022	[PUB] [PDF]
Decentralized Graph Federated Multitask Learning for Streaming Data	NTNU	CISS	2022	[PUB]
Neural graph collaborative filtering for privacy preservation based on federated transfer learning		Electron. Libr.	2022	[PUB]
Dynamic Neural Graphs Based Federated Reptile for Semi-Supervised Multi-Tasking in Healthcare Applications	Oxford	JBHI	2022	[PUB]
FedGCN: Federated Learning-Based Graph Convolutional Networks for Non-Euclidean Spatial Data	NUIST	Mathematics	2022	[PUB]
Federated Dynamic Graph Neural Networks with Secure Aggregation for Video-based Distributed Surveillance	ND	ACM Trans. Intell. Syst. Technol.	2022	[PUB] [PDF] [解读]
Device Sampling for Heterogeneous Federated Learning: Theory, Algorithms, and Implementation.	Purdue	INFOCOM	2021	[PUB] [PDF]
Federated Graph Classification over Non-IID Graphs	Emory	NeurIPS	2021	[PUB] [PDF] [CODE] [解读]
Subgraph Federated Learning with Missing Neighbor Generation	Emory; UBC; Lehigh University	NeurIPS	2021	[PUB] [PDF]
Cross-Node Federated Graph Neural Network for Spatio-Temporal Data Modeling	USC	KDD	2021	[PUB] [PDF] [CODE] [解读]
Differentially Private Federated Knowledge Graphs Embedding `kg.`	BUAA	CIKM	2021	[PUB] [PDF] [CODE] [解读]
Decentralized Federated Graph Neural Networks	Blue Elephant Tech	IJCAI Workshop	2021	[PDF]
FedSGC: Federated Simple Graph Convolution for Node Classification	HKUST	IJCAI Workshop	2021	[PDF]
FL-DISCO: Federated Generative Adversarial Network for Graph-based Molecule Drug Discovery: Special Session Paper	UNM	ICCAD	2021	[PUB]
FASTGNN: A Topological Information Protected Federated Learning Approach for Traffic Speed Forecasting	UTS	IEEE Trans. Ind. Informatics	2021	[PUB]
DAG-FL: Direct Acyclic Graph-based Blockchain Empowers On-Device Federated Learning	BUPT; UESTC	ICC	2021	[PUB] [PDF]
FedE: Embedding Knowledge Graphs in Federated Setting `kg.`	ZJU	IJCKG	2021	[PUB] [PDF] [CODE]
Federated Knowledge Graph Embeddings with Heterogeneous Data `kg.`	TJU	CCKS	2021	[PUB]
A Graph Federated Architecture with Privacy Preserving Learning	EPFL	SPAWC	2021	[PUB] [PDF] [解读]
Federated Social Recommendation with Graph Neural Network	UIC	ACM TIST	2021	[PUB] [PDF] [CODE]
FedGraphNN: A Federated Learning System and Benchmark for Graph Neural Networks `surv.`	USC	ICLR Workshop / MLSys Workshop	2021	[PDF] [CODE] [解读]
A Federated Multigraph Integration Approach for Connectional Brain Template Learning	Istanbul Technical University	MICCAI Workshop	2021	[PUB] [CODE]
Cluster-driven Graph Federated Learning over Multiple Domains	Politecnico di Torino	CVPR Workshop	2021	[PDF] [解读]
FedGNN: Federated Graph Neural Network for Privacy-Preserving Recommendation	THU	ICML workshop	2021	[PDF] [解读]
Decentralized federated learning of deep neural networks on non-iid data	RISE; Chalmers University of Technology	ICML workshop	2021	[PDF] [CODE]
Glint: Decentralized Federated Graph Learning with Traffic Throttling and Flow Scheduling	The University of Aizu	IWQoS	2021	[PUB]
Federated Graph Neural Network for Cross-graph Node Classification	BUPT	CCIS	2021	[PUB]
GraFeHTy: Graph Neural Network using Federated Learning for Human Activity Recognition	Lead Data Scientist Ericsson Digital Services	ICMLA	2021	[PUB]
Distributed Training of Graph Convolutional Networks	Sapienza University of Rome	TSIPN	2021	[PUB] [PDF] [解读]
Decentralized federated learning for electronic health records	UMN	NeurIPS Workshop / CISS	2020	[PUB] [PDF] [解读]
ASFGNN: Automated Separated-Federated Graph Neural Network	Ant Group	PPNA	2020	[PUB] [PDF] [解读]
Decentralized federated learning via sgd over wireless d2d networks	SZU	SPAWC	2020	[PUB] [PDF]
SGNN: A Graph Neural Network Based Federated Learning Approach by Hiding Structure	SDU	BigData	2019	[PUB] [PDF]
Towards Federated Graph Learning for Collaborative Financial Crimes Detection	IBM	NeurIPS Workshop	2019	[PDF]
Federated learning of predictive models from federated Electronic Health Records	BU	Int. J. Medical Informatics	2018	[PUB]
FedHGN: A Federated Framework for Heterogeneous Graph Neural Networks.		preprint	2023	[PDF] [CODE]
Graph-guided Personalization for Federated Recommendation.		preprint	2023	[PDF]
GraphGANFed: A Federated Generative Framework for Graph-Structured Molecules Towards Efficient Drug Discovery.		preprint	2023	[PDF]
GLASU: A Communication-Efficient Algorithm for Federated Learning with Vertically Distributed Graph Data		preprint	2023	[PDF]
Vertical Federated Graph Neural Network for Recommender System		preprint	2023	[PDF] [CODE]
Lumos: Heterogeneity-aware Federated Graph Learning over Decentralized Devices		preprint	2023	[PDF]
Securing IoT Communication using Physical Sensor Data - Graph Layer Security with Federated Multi-Agent Deep Reinforcement Learning.		preprint	2023	[PDF]
Heterogeneous Federated Knowledge Graph Embedding Learning and Unlearning.		preprint	2023	[PDF]
Uplink Scheduling in Federated Learning: an Importance-Aware Approach via Graph Representation Learning		preprint	2023	[PDF]
Graph Federated Learning with Hidden Representation Sharing	UCLA	preprint	2022	[PDF]
M3FGM:a node masking and multi-granularity message passing-based federated graph model for spatial-temporal data prediction	Xidian University	preprint	2022	[PDF]
Federated Graph-based Networks with Shared Embedding	BUCEA	preprint	2022	[PDF]
Privacy-preserving Decentralized Federated Learning over Time-varying Communication Graph	Lancaster University	preprint	2022	[PDF]
Heterogeneous Federated Learning on a Graph.		preprint	2022	[PDF]
FedEgo: Privacy-preserving Personalized Federated Graph Learning with Ego-graphs	SYSU	preprint	2022	[PDF] [CODE]
Federated Graph Contrastive Learning	UTS	preprint	2022	[PDF]
FD-GATDR: A Federated-Decentralized-Learning Graph Attention Network for Doctor Recommendation Using EHR		preprint	2022	[PDF]
Privacy-preserving Graph Analytics: Secure Generation and Federated Learning		preprint	2022	[PDF]
Federated Graph Attention Network for Rumor Detection		preprint	2022	[PDF] [CODE]
FedRel: An Adaptive Federated Relevance Framework for Spatial Temporal Graph Learning		preprint	2022	[PDF]
Privatized Graph Federated Learning		preprint	2022	[PDF]
Federated Graph Neural Networks: Overview, Techniques and Challenges `surv.`		preprint	2022	[PDF]
Decentralized event-triggered federated learning with heterogeneous communication thresholds.		preprint	2022	[PDF]
Federated Learning with Heterogeneous Architectures using Graph HyperNetworks		preprint	2022	[PDF]
STFL: A Temporal-Spatial Federated Learning Framework for Graph Neural Networks		preprint	2021	[PDF] [CODE]
PPSGCN: A Privacy-Preserving Subgraph Sampling Based Distributed GCN Training Method		preprint	2021	[PDF]
Leveraging a Federation of Knowledge Graphs to Improve Faceted Search in Digital Libraries `kg.`		preprint	2021	[PDF]
Federated Myopic Community Detection with One-shot Communication		preprint	2021	[PDF]
Federated Graph Learning -- A Position Paper `surv.`		preprint	2021	[PDF]
A Vertical Federated Learning Framework for Graph Convolutional Network		preprint	2021	[PDF]
FedGL: Federated Graph Learning Framework with Global Self-Supervision		preprint	2021	[PDF]
FL-AGCNS: Federated Learning Framework for Automatic Graph Convolutional Network Search		preprint	2021	[PDF]
A New Look and Convergence Rate of Federated Multi-Task Learning with Laplacian Regularization		preprint	2021	[PDF] [CODE]
Improving Federated Relational Data Modeling via Basis Alignment and Weight Penalty `kg.`		preprint	2020	[PDF]
GraphFederator: Federated Visual Analysis for Multi-party Graphs		preprint	2020	[PDF]
Privacy-Preserving Graph Neural Network for Node Classification		preprint	2020	[PDF]
Peer-to-peer federated learning on graphs	UC	preprint	2019	[PDF] [解读]

Private Graph Neural Networks (todo)

[Arxiv 2021] Privacy-Preserving Graph Convolutional Networks for Text Classification. [PDF]
[Arxiv 2021] GraphMI: Extracting Private Graph Data from Graph Neural Networks. [PDF]
[Arxiv 2021] Towards Representation Identical Privacy-Preserving Graph Neural Network via Split Learning. [PDF]
[Arxiv 2020] Locally Private Graph Neural Networks. [PDF]

Private Graph Neural Networks (todo)

fl on tabular data

This section refers to DBLP search engine.

fl on tabular data

Title	Affiliation	Venue	Year	Materials
SGBoost: An Efficient and Privacy-Preserving Vertical Federated Tree Boosting Framework	Xidian University	IEEE Trans. Inf. Forensics Secur.	2023	[PUB] [CODE]
Incentive-boosted Federated Crowdsourcing	SDU	AAAI	2023	[PDF]
Explaining predictions and attacks in federated learning via random forests	Universitat Rovira i Virgili	Appl. Intell.	2023	[PUB] [CODE]
Boosting Accuracy of Differentially Private Federated Learning in Industrial IoT With Sparse Responses		IEEE Trans. Ind. Informatics	2023	[PUB]
Driver Drowsiness EEG Detection Based on Tree Federated Learning and Interpretable Network.		Int. J. Neural Syst.	2023	[PUB]
FDPBoost: Federated differential privacy gradient boosting decision trees.		J. Inf. Secur. Appl.	2023	[PUB]
Gradient-less Federated Gradient Boosting Trees with Learnable Learning Rates.		EuroMLSys	2023	[PUB] [PDF]
HT-Fed-GAN: Federated Generative Model for Decentralized Tabular Data Synthesis	HIT	Entropy	2023	[PUB]
Blockchain-Based Swarm Learning for the Mitigation of Gradient Leakage in Federated Learning	University of Udine	IEEE Access	2023	[PUB]
OpBoost: A Vertical Federated Tree Boosting Framework Based on Order-Preserving Desensitization	ZJU	Proc. VLDB Endow.	2022	[PUB] [PDF] [CODE]
RevFRF: Enabling Cross-Domain Random Forest Training With Revocable Federated Learning	XIDIAN UNIVERSITY	IEEE Trans. Dependable Secur. Comput.	2022	[PUB] [PDF]
A Tree-based Model Averaging Approach for Personalized Treatment Effect Estimation from Heterogeneous Data Sources	University of Pittsburgh	ICML	2022	[PUB] [PDF] [CODE]
Federated Boosted Decision Trees with Differential Privacy	University of Warwick	CCS	2022	[PUB] [PDF] [CODE]
Federated Functional Gradient Boosting	University of Pennsylvania	AISTATS	2022	[PUB] [PDF] [CODE]
Tree-Based Models for Federated Learning Systems.	IBM Research	Federated Learning	2022	[PUB]
Federated Learning for Tabular Data using TabNet: A Vehicular Use-Case		ICCP	2022	[PUB]
Federated Learning for Tabular Data: Exploring Potential Risk to Privacy	Newcastle University	ISSRE	2022	[PDF]
Federated Random Forests can improve local performance of predictive models for various healthcare applications	University of Marburg	Bioinform.	2022	[PUB] [CODE]
FLForest: Byzantine-robust Federated Learning through Isolated Forest	NUAA	ICPADS	2022	[PUB]
Boosting the Federation: Cross-Silo Federated Learning without Gradient Descent.	unito	IJCNN	2022	[PUB] [CODE]
Federated Forest	JD	TBD	2022	[PUB] [PDF]
Sliding Focal Loss for Class Imbalance Classification in Federated XGBoost.	Swinburne University of Technology	ISPA/BDCloud/SocialCom/SustainCom	2022	[PUB]
Neural gradient boosting in federated learning for hemodynamic instability prediction: towards a distributed and scalable deep learning-based solution.		AMIA	2022	[PUB]
Fed-GBM: a cost-effective federated gradient boosting tree for non-intrusive load monitoring	The University of Sydney	e-Energy	2022	[PUB]
Verifiable Privacy-Preserving Scheme Based on Vertical Federated Random Forest	NUST	IEEE Internet Things J.	2022	[PUB]
Statistical Detection of Adversarial examples in Blockchain-based Federated Forest In-vehicle Network Intrusion Detection Systems	CNU	IEEE Access	2022	[PUB] [PDF]
BOFRF: A Novel Boosting-Based Federated Random Forest Algorithm on Horizontally Partitioned Data	METU	IEEE Access	2022	[PUB]
eFL-Boost: Efficient Federated Learning for Gradient Boosting Decision Trees	kobe-u	IEEE Access	2022	[PUB]
An Efficient Learning Framework for Federated XGBoost Using Secret Sharing and Distributed Optimization	TJU	ACM Trans. Intell. Syst. Technol.	2022	[PUB] [PDF] [CODE]
An optional splitting extraction based gain-AUPRC balanced strategy in federated XGBoost for mitigating imbalanced credit card fraud detection	Swinburne University of Technology	Int. J. Bio Inspired Comput.	2022	[PUB]
Random Forest Based on Federated Learning for Intrusion Detection	Malardalen University	AIAI	2022	[PUB]
Cross-silo federated learning based decision trees	ETH Zürich	SAC	2022	[PUB]
Leveraging Spanning Tree to Detect Colluding Attackers in Federated Learning	Missouri S&T	INFCOM Workshops	2022	[PUB]
VF2Boost: Very Fast Vertical Federated Gradient Boosting for Cross-Enterprise Learning	PKU	SIGMOD	2021	[PUB]
Boosting with Multiple Sources	Google	NeurIPS	2021	[PUB]
SecureBoost: A Lossless Federated Learning Framework	UC	IEEE Intell. Syst.	2021	[PUB] [PDF] [SLIDE] [CODE] [解读] [UC]
A Blockchain-Based Federated Forest for SDN-Enabled In-Vehicle Network Intrusion Detection System	CNU	IEEE Access	2021	[PUB]
Research on privacy protection of multi source data based on improved gbdt federated ensemble method with different metrics	NCUT	Phys. Commun.	2021	[PUB]
Fed-EINI: An Efficient and Interpretable Inference Framework for Decision Tree Ensembles in Vertical Federated Learning	UCAS; CAS	IEEE BigData	2021	[PUB] [PDF]
Gradient Boosting Forest: a Two-Stage Ensemble Method Enabling Federated Learning of GBDTs	THU	ICONIP	2021	[PUB]
A k-Anonymised Federated Learning Framework with Decision Trees	Umeå University	DPM/CBT @ESORICS	2021	[PUB]
AF-DNDF: Asynchronous Federated Learning of Deep Neural Decision Forests	Chalmers	SEAA	2021	[PUB]
Compression Boosts Differentially Private Federated Learning	Univ. Grenoble Alpes	EuroS&P	2021	[PUB] [PDF]
Practical Federated Gradient Boosting Decision Trees	NUS; UWA	AAAI	2020	[PUB] [PDF] [CODE]
Privacy Preserving Vertical Federated Learning for Tree-based Models	NUS	VLDB	2020	[PUB] [PDF] [VIDEO] [CODE]
Boosting Privately: Federated Extreme Gradient Boosting for Mobile Crowdsensing	Xidian University	ICDCS	2020	[PUB] [PDF]
FedCluster: Boosting the Convergence of Federated Learning via Cluster-Cycling	University of Utah	IEEE BigData	2020	[PUB] [PDF]
New Approaches to Federated XGBoost Learning for Privacy-Preserving Data Analysis	kobe-u	ICONIP	2020	[PUB]
Bandwidth Slicing to Boost Federated Learning Over Passive Optical Networks	Chalmers University of Technology	IEEE Communications Letters	2020	[PUB]
DFedForest: Decentralized Federated Forest	UFRJ	Blockchain	2020	[PUB]
Straggler Remission for Federated Learning via Decentralized Redundant Cayley Tree	Stevens Institute of Technology	LATINCOM	2020	[PUB]
Federated Soft Gradient Boosting Machine for Streaming Data	Sinovation Ventures AI Institute	Federated Learning	2020	[PUB] [解读]
Federated Learning of Deep Neural Decision Forests	Fraunhofer-Chalmers Centre	LOD	2019	[PUB]
Privet: A Privacy-Preserving Vertical Federated Learning Service for Gradient Boosted Decision Tables.		preprint	2023	[PDF]
V2X-Boosted Federated Learning for Cooperative Intelligent Transportation Systems with Contextual Client Selection.		preprint	2023	[PDF]
GTV: Generating Tabular Data via Vertical Federated Learning		preprint	2023	[PDF]
Federated Survival Forests		preprint	2023	[PDF]
Fed-TDA: Federated Tabular Data Augmentation on Non-IID Data	HIT	preprint	2022	[PDF]
Data Leakage in Tabular Federated Learning	ETH Zurich	preprint	2022	[PDF]
Boost Decentralized Federated Learning in Vehicular Networks by Diversifying Data Sources		preprint	2022	[PDF]
Federated XGBoost on Sample-Wise Non-IID Data		preprint	2022	[PDF]
Hercules: Boosting the Performance of Privacy-preserving Federated Learning		preprint	2022	[PDF]
FedGBF: An efficient vertical federated learning framework via gradient boosting and bagging		preprint	2022	[PDF]
A Fair and Efficient Hybrid Federated Learning Framework based on XGBoost for Distributed Power Prediction.	THU	preprint	2022	[PDF]
An Efficient and Robust System for Vertically Federated Random Forest		preprint	2022	[PDF]
Efficient Batch Homomorphic Encryption for Vertically Federated XGBoost.	BUAA	preprint	2021	[PDF]
Guess what? You can boost Federated Learning for free		preprint	2021	[PDF]
SecureBoost+ : A High Performance Gradient Boosting Tree Framework for Large Scale Vertical Federated Learning		preprint	2021	[PDF] [CODE]
Fed-TGAN: Federated Learning Framework for Synthesizing Tabular Data		preprint	2021	[PDF]
FedXGBoost: Privacy-Preserving XGBoost for Federated Learning	TUM	preprint	2021	[PDF]
Adaptive Histogram-Based Gradient Boosted Trees for Federated Learning		preprint	2020	[PDF]
FederBoost: Private Federated Learning for GBDT	ZJU	preprint	2020	[PDF]
Privacy Preserving Text Recognition with Gradient-Boosting for Federated Learning		preprint	2020	[PDF] [CODE]
Cloud-based Federated Boosting for Mobile Crowdsensing		preprint	2020	[ARXIV]
Federated Extra-Trees with Privacy Preserving		preprint	2020	[PDF]
Bandwidth Slicing to Boost Federated Learning in Edge Computing		preprint	2019	[PDF]
Revocable Federated Learning: A Benchmark of Federated Forest		preprint	2019	[PDF]
The Tradeoff Between Privacy and Accuracy in Anomaly Detection Using Federated XGBoost	CUHK	preprint	2019	[PDF] [CODE]

framework

federated learning framework

table

Note: SG means Support for Graph data and algorithms, ST means Support for Tabular data and algorithms.

federated learning framework

Platform	Papers	Affiliations	Materials
PySyft	A generic framework for privacy preserving deep learning	OpenMined	[DOC]
FATE	FATE: An Industrial Grade Platform for Collaborative Learning With Data Protection	WeBank	[DOC] [DOC(ZH)]
FedML	FedML: A Research Library and Benchmark for Federated Machine Learning	FedML	[DOC]
Flower	Flower: A Friendly Federated Learning Research Framework	flower.dev adap	[DOC]
TFF(Tensorflow-Federated)	Towards Federated Learning at Scale: System Design	Google	[DOC] [PAGE]
SecretFlow		Ant group	[DOC]
Primihub		primihub	[DOC]
FederatedScope	FederatedScope: A Flexible Federated Learning Platform for Heterogeneity	Alibaba DAMO Academy	[DOC] [PAGE]
PFLlib	FedALA: Adaptive Local Aggregation for Personalized Federated Learning	SJTU
Fedlearner		Bytedance
LEAF	LEAF: A Benchmark for Federated Settings	CMU
OpenFL	OpenFL: An open-source framework for Federated Learning	Intel	[DOC]
Fedlab	FedLab: A Flexible Federated Learning Framework	SMILELab	[DOC] [DOC(ZH)] [PAGE]
Rosetta		matrixelements	[DOC] [PAGE]
Privacy Meter	Comprehensive Privacy Analysis of Deep Learning: Passive and Active White-box Inference Attacks against Centralized and Federated Learning	University of Massachusetts Amherst
PaddleFL		Baidu	[DOC]
NIID-Bench	Federated Learning on Non-IID Data Silos: An Experimental Study	Xtra Computing Group
NVFlare		NVIDIA	[DOC]
IBM Federated Learning	IBM Federated Learning: an Enterprise Framework White Paper	IBM	[PAPERS]
KubeFATE		WeBank	[WIKI]
easyFL	Federated Learning with Fair Averaging	XMU
FedScale	FedScale: Benchmarking Model and System Performance of Federated Learning at Scale	SymbioticLab(U-M)
Differentially Private Federated Learning: A Client-level Perspective	Differentially Private Federated Learning: A Client Level Perspective	SAP-samples
Backdoors 101	Blind Backdoors in Deep Learning Models	Cornell Tech
plato		UofT
SWARM LEARNING	Swarm Learning for decentralized and confidential clinical machine learning		[VIDEO]
substra		Substra	[DOC]
FedJAX	FEDJAX: Federated learning simulation with JAX	Google
Galaxy Federated Learning	GFL: A Decentralized Federated Learning Framework Based On Blockchain	ZJU	[DOC]
FedNLP	FedNLP: Benchmarking Federated Learning Methods for Natural Language Processing Tasks	FedML
EasyFL	EasyFL: A Low-code Federated Learning Platform For Dummies	NTU
Breaching	A Framework for Attacks against Privacy in Federated Learning (papers)
FLSim		facebook research
SyferText		OpenMined
PyVertical	PyVertical: A Vertical Federated Learning Framework for Multi-headed SplitNN	OpenMined
Xaynet		XayNet	[PAGE] [DOC] [WHITEPAPER] [LEGAL REVIEW]
FedGraphNN	FedGraphNN: A Federated Learning System and Benchmark for Graph Neural Networks	FedML
FLUTE	FLUTE: A Scalable, Extensible Framework for High-Performance Federated Learning Simulations	microsoft	[DOC]
FLSim	Optimizing Federated Learning on Non-IID Data with Reinforcement Learning	University of Toronto
FedTorch	Distributionally Robust Federated Averaging	Penn State
PhotoLabeller			[BLOG]
FATE-Serving		WeBank	[DOC]
PriMIA	End-to-end privacy preserving deep learning on multi-institutional medical imaging	TUM; Imperial College London; OpenMined	[DOC]
FedTree	FedTree: A Federated Learning System For Trees	Xtra Computing Group	[DOC]
FEDn	Scalable federated machine learning with FEDn	scaleoutsystems	[DOC]
9nfl		JD
FedLearn	Fedlearn-Algo: A flexible open-source privacy-preserving machine learning platform	JD
FeTS	The federated tumor segmentation (FeTS) tool: an open-source solution to further solid tumor research	Federated Tumor Segmentation (FeTS) initiative	[DOC]
FedCV	FedCV: A Federated Learning Framework for Diverse Computer Vision Tasks	FedML
MPLC		LabeliaLabs	[PAGE]
APPFL			[DOC]
FlexCFL	Flexible Clustered Federated Learning for Client-Level Data Distribution Shift	Chongqing University
Flame		Cisco	[DOC]
FedGroup	FedGroup: Efficient Clustered Federated Learning via Decomposed Data-Driven Measure	Chongqing University
FedEval	FedEval: A Benchmark System with a Comprehensive Evaluation Model for Federated Learning	HKU	[DOC]
UCADI	Advancing COVID-19 diagnosis with privacy-preserving collaboration in artificial intelligence	Huazhong University of Science and Technology
OpenFed	OpenFed: A Comprehensive and Versatile Open-Source Federated Learning Framework		[DOC]
FedSim
Federated-Learning-source	A Practical Federated Learning Framework for Small Number of Stakeholders	ETH Zürich	[DOC]
Clara		NVIDIA
OpenHealth		ZJU

benchmark

UniFed leaderboard

Here's a really great Benchmark for the federated learning open source framework UniFed leaderboard, which present both qualitative and quantitative evaluation results of existing popular open-sourced FL frameworks, from the perspectives of functionality, usability, and system performance.

workflow-design

UniFed_framework_benchmark

For more results, please refer to Framework Functionality Support

datasets

fl graph datasets

Wyze Rule Dataset

tabular datasets

fl datasets

surveys

This section partially refers to repository Federated-Learning and FederatedAI research , the order of the surveys is arranged in reverse order according to the time of first submission (the latest being placed at the top)

[Ad Hoc Networks 2024] Privacy Computing Meets Metaverse: Necessity, Taxonomy and Challenges PUB PDF CODE
[SIGKDD Explor. 2022] Federated Graph Machine Learning: A Survey of Concepts, Techniques, and Applications PUB PDF
[ACM Trans. Interact. Intell. Syst.] Toward Responsible AI: An Overview of Federated Learning for User-centered Privacy-preserving Computing PUB
[ICML Workshop 2020] SECure: A Social and Environmental Certificate for AI Systems PDF
[IEEE Commun. Mag. 2020] From Federated Learning to Fog Learning: Towards Large-Scale Distributed Machine Learning in Heterogeneous Wireless Networks PDF [PUB]
[China Communications 2020] Federated Learning for 6G Communications: Challenges, Methods, and Future Directions PDF PUB
[Federated Learning Systems] A Review of Privacy Preserving Federated Learning for Private IoT Analytics PDF [PUB]
[WorldS4 2020] Survey of Personalization Techniques for Federated Learning PDF PUB
Towards Utilizing Unlabeled Data in Federated Learning: A Survey and Prospective PDF
[IEEE Internet Things J. 2022] A Survey on Federated Learning for Resource-Constrained IoT Devices PDF PUB
[IEEE Communications Surveys & Tutorials 2020] Communication-Efficient Edge AI: Algorithms and Systems PDF PUB
[IEEE Communications Surveys & Tutorials 2020] Federated Learning in Mobile Edge Networks: A Comprehensive Survey PDF PUB
[IEEE Signal Process. Mag. 2020] Federated Learning: Challenges, Methods, and Future Directions PDF [PUB]
[IEEE Commun. Mag. 2020] Federated Learning for Wireless Communications: Motivation, Opportunities and Challenges PDF PUB
[IEEE TKDE 2021] A Survey on Federated Learning Systems: Vision, Hype and Reality for Data Privacy and Protection PDF PUB
[IJCAI Workshop 2020] Threats to Federated Learning: A Survey PDF
[Foundations and Trends in Machine Learning 2021] Advances and Open Problems in Federated Learning PDF PUB
Privacy-Preserving Blockchain Based Federated Learning with Differential Data Sharing PDF
An Introduction to Communication Efficient Edge Machine Learning PDF
[IEEE Communications Surveys & Tutorials 2020] Convergence of Edge Computing and Deep Learning: A Comprehensive Survey PDF PUB
[IEEE TIST 2019] Federated Machine Learning: Concept and Applications PDF [PUB]
[J. Heal. Informatics Res. 2021] Federated Learning for Healthcare Informatics PDF PUB
Federated Learning for Coalition Operations PDF
No Peek: A Survey of private distributed deep learning PDF

tutorials and courses

tutorials

联邦学习入门教程参考
[NeurIPS 2020] Federated Learning Tutorial [Web] [Slides] [Video]
Federated Learning on MNIST using a CNN, AI6101, 2020 (Demo Video)
[AAAI 2019] Federated Learning: User Privacy, Data Security and Confidentiality in Machine Learning
Applied Cryptography
A Brief Introduction to Differential Privacy
Deep Learning with Differential Privacy.
Building Safe A.I.
- A Tutorial for Encrypted Deep Learning
- Use Homomorphic Encryption (HE)
Private Image Analysis with MPC
- Training CNNs on Sensitive Data
- Use SPDZ as MPC protocol
Private Deep Learning with MPC
- A Simple Tutorial from Scratch
- Use Multiparty Compuation (MPC)

course

Simple Introduction to Sharmir's Secret Sharing and Lagrange Interpolation
Secret Sharing
- Part 1: Shamir's Secret Sharing & Packed Variant
- Part 2: Improve efficiency
- Part 3: Robust Reconstruction

key conferences/workshops/journals

This section partially refers to The Federated Learning Portal.

workshops

[FL@FM-NeurIPS'23],International Workshop on Federated Learning in the Age of Foundation Models in Conjunction with NeurIPS 2023(FL@FM-NeurIPS’23), New Orleans, LA, USA
[FL-CVPR'23], 2nd Workshop on Federated Learning for Computer Vision
[FL-IJCAI'23], International Workshop on Trustworthy Federated Learning in Conjunction with IJCAI 2023 (FL-IJCAI'23), Macau
[FL-KDD'23], International Workshop on Federated Learning for Distributed Data Mining Co-located with the 29th ACM SIGKDD Conference (KDD 2023), Long Beach, CA, USA
[FL-ICML'23],Federated Learning and Analytics in Practice: Algorithms, Systems, Applications, and Opportunities Workshop at ICML 2023, Honolulu, HI, USA
[FLIRT-SIGIR'23],1st Workshop on Federated Learning for Information ReTrieval, Taipei, Taiwan
[FLSys'23], the Federated Learning Systems (FLSys) Workshop @ MLSys 2023, Miami, FL, USA
[FLW@TheWebConf'23], 1st Workshop on Federated Learning Technologies, Austin, TX, USA
[CIKM'22] The 1st International Workshop on Federated Learning with Graph Data (FedGraph), Atlanta, GA, USA
[AI Technology School 2022] Trustable, Verifiable and Auditable Artificial Intelligence, Singapore
[FL-CVPR'22] First International Workshop on Federated Learning for Computer Vision (FedVision)
[FL-NeurIPS'22] International Workshop on Federated Learning: Recent Advances and New Challenges in Conjunction with NeurIPS 2022 , New Orleans, LA, USA
[FL-IJCAI'22] International Workshop on Trustworthy Federated Learning in Conjunction with IJCAI 2022, Vienna, Austria
[FL-AAAI-22] International Workshop on Trustable, Verifiable and Auditable Federated Learning in Conjunction with AAAI 2022, Vancouver, BC, Canada (Virtual)
[FL-MobiCom'22] FedEdge 2022, 1st ACM Workshop on Data Privacy and Federated Learning Technologies for Mobile Edge Network -Research Track, Sydney, Australia
[FL-NeurIPS'21] New Frontiers in Federated Learning: Privacy, Fairness, Robustness, Personalization and Data Ownership, (Virtual)
[The Federated Learning Workshop, 2021] , Paris, France (Hybrid)
[PDFL-EMNLP'21] Workshop on Parallel, Distributed, and Federated Learning, Bilbao, Spain (Virtual)
[FTL-IJCAI'21] International Workshop on Federated and Transfer Learning for Data Sparsity and Confidentiality in Conjunction with IJCAI 2021, Montreal, QB, Canada (Virtual)
[DeepIPR-IJCAI'21] Toward Intellectual Property Protection on Deep Learning as a Services, Montreal, QB, Canada (Virtual)
[FL-ICML'21] International Workshop on Federated Learning for User Privacy and Data Confidentiality, (Virtual)
[RSEML-AAAI-21] Towards Robust, Secure and Efficient Machine Learning, (Virtual)
[NeurIPS-SpicyFL'20] Workshop on Scalability, Privacy, and Security in Federated Learning, Vancouver, BC, Canada (Virtual)
[FL-IJCAI'20] International Workshop on Federated Learning for User Privacy and Data Confidentiality, Yokohama, Japan (Virtual)
[FL-ICML'20] International Workshop on Federated Learning for User Privacy and Data Confidentiality, Vienna, Austria (Virtual)
[FL-IBM'20] Workshop on Federated Learning and Analytics, New York, NY, USA
[FL-NeurIPS'19] Workshop on Federated Learning for Data Privacy and Confidentiality (in Conjunction with NeurIPS 2019), Vancouver, BC, Canada
[FL-IJCAI'19] International Workshop on Federated Learning for User Privacy and Data Confidentiality in Conjunction with IJCAI 2019, Macau
[FL-Google'19] Workshop on Federated Learning and Analytics, Seattle, WA, USA

journal special issues

Special Issue on Trustable, Verifiable, and Auditable Federated Learning, IEEE Transactions on Big Data (TBD), 2022.
Special Issue on Federated Learning: Algorithms, Systems, and Applications, ACM Transactions on Intelligent Systems and Technology (TIST), 2021.
Special Issue on Federated Machine Learning, IEEE Intelligent Systems (IS), 2019.

conference special tracks

"Federated Learning" included as a new keyword in IJCAI'20, Yokohama, Japan
Special Track on Federated Machine Learning, IEEE BigData'19, Los Angeles, CA, USA

update log

2024/04/15 - add TPAMI, VLDB 2024 papers
2024/04/10 - add WSDM, Mach Learn 2024 papers
2024/03/28 - add AAAI, TC, TPAMI, TPDS, VLDB 2024 papers
2024/03/08 - add TPAMI, TC, TCAD 2024 papers
2024/02/23 - add ICLR 2024 papers
2024/01/02 - add NeurIPS 2023 papers
2023/12/13 - add MM, CCS, EMNLP 2023 papers and update VLDB, TC, TCAD papers
2023/10/07 - add ICCV 2023 papers
2023/09/18 - add INFOCOM, S&P 2023 papers
2023/08/18 - add COLT 2023 paper
2023/08/16 - refresh KDD, IJCAI 2023 papers
2023/08/02 - refresh ICML 2023 information
2023/07/31 - add MobiCom, ICDE, EuroSys, USENIX Security 2023 papers
2023/07/24 - add SIGIR, UAI, ICSE 2023 papers and information on CVPR workshops
2023/07/03 - add Events for different conferences and journals like ACL
2023/07/01 - add AAAI, ICML, IJCAI, SIGIR, KDD, ACL 2023 papers
2023/06/28 - add AISTATS, MLsys, JMLR, Machine Learning, ALT, FOCS, STOC papers
2023/06/06 - remove 'tldr information' and change this repo from "Awesome-Federated-Learning-on-Graph-and-Tabular-Data" into "Awesome-FL".
2023/05/23 - add CVPR 2023 papers
2023/05/07 - add workshops and WWW 2023 papers
2023/04/02 - add NDSS 2023 papers and fix some typos
2023/02/19 - add INFOCOM 2023 papers
2023/02/14 - add EMNLP 2022 papers
2023/02/13 - add ICLR 2023 papers
2023/01/14 - add UAI 2022 papers, refresh system (TCAD +1, TPDS+8), ML (TPAMI +1,UAI +6), network(MobiCom +3) fields papers
2022/11/24 - refresh NeurIPS 2022,2021 and ICLR 2022 papers
2022/11/06- add S&P 2023 papers
2022/10/29 - add WSDM 2023 paper
2022/10/20 - add CCS, MM, ECCV 2022 papers
2022/10/16 - add AI, JMLR, TPAMI, IJCV, TOCS, TOS, TCAD, TC papers
2022/10/13 - add DAC papers
2022/10/09 - add MobiCom 2022 paper
2022/09/19 - add NeurIPS 2022 papers
2022/09/16 - repository is online with Github Pages
2022/09/06 - add information about FL on Tabular and Graph data
2022/09/05 - add some information about top journals and add TPDS papers
2022/08/31 - all papers (including 400+ papers from top conferences and top journals and 100+ papers with graph and tabular data) have been comprehensively sorted out, and information such as publication addresses, links to preprints and source codes of these papers have been compiled. The source code of 280+ papers has been obtained. We hope it can help those who use this project.
2022/07/31 - add VLDB papers
2022/07/30 - add top-tier system conferences papers and add COLT,UAI,OSDI, SOSP, ISCA, MLSys, AISTATS,WSDM papers
2022/07/28 - add a list of top-tier conferences papers and add IJCAI,SIGIR,SIGMOD,ICDE,WWW,SIGCOMM.INFOCOM,WWW papers
2022/07/27 - add some ECCV 2022 papers
2022/07/22 - add CVPR 2022 and MM 2020,2021 papers
2022/07/21 - give TL;DR and interpret information(解读) of papers. And add KDD 2022 papers
2022/07/15 - give a list of papers in the field of federated learning in top NLP/Secure conferences. And add ICML 2022 papers
2022/07/14 - give a list of papers in the field of federated learning in top ML/CV/AI/DM conferences from innovation-cat‘s Awesome-Federated-Machine-Learning and find papers(code is available & stars >= 100)
2022/07/12 - added information about the last commit time of the federated learning open source framework (can be used to determine the maintenance of the code base)
2022/07/12 - give a list of papers in the field of federated learning in top journals
2022/05/25 - complete the paper and code lists of FL on tabular data and Tree algorithms
2022/05/25 - add the paper list of FL on tabular data and Tree algorithms
2022/05/24 - complete the paper and code lists of FL on graph data and Graph Neural Networks
2022/05/23 - add the paper list of FL on graph data and Graph Neural Networks
2022/05/21 - update all of Federated Learning Framework

acknowledgments

Many thanks to the other awesome list:

citation

@misc{Awesome-FL,
    title = {Awesome-FL},
    author = {Yuwen Yang, Bingjie Yan, Xuefeng Jiang, Hongcheng Li, Jian Wang, Jiao Chen, Xiangmou Qu, Chang Liu and others},
    year = {2022},
    howpublished = {\\url{https://github.com/youngfish42/Awesome-FL}
}

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Awesome-FL

Federated Learning Resources

papers

fl in top-tier journal

fl in top ai conference and journal

fl in top ml conference and journal

fl in top dm conference and journal

fl in top secure conference and journal

fl in top cv conference and journal

fl in top nlp conference and journal

fl in top ir conference and journal

fl in top db conference and journal

fl in top network conference and journal

fl in top system conference and journal

fl in top conference and journal other fields

fl on graph data and graph neural networks

Private Graph Neural Networks (todo)

fl on tabular data

framework

federated learning framework

table

benchmark

datasets

fl graph datasets

tabular datasets

fl datasets

surveys

tutorials and courses

tutorials

course

secret sharing

key conferences/workshops/journals

workshops

journal special issues

conference special tracks

update log

acknowledgments

citation