youngfish42/Awesome-FL youngfish42/Awesome-FL

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  • Language
    Python
  • License
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  • Created over 2 years ago
  • Updated 10 months ago
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Repository Details

Comprehensive and timely academic information on federated learning (papers, frameworks, datasets, tutorials, workshops)

Federated Learning Resources

Stars Awesome License

Table of Contents

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 @ ([email protected]). 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, TPDS, DAC, TOCS, TOS, TCAD, TC)

  • Others (ICSE, FOCS, STOC)

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

keywords

Statistics: ๐Ÿ”ฅ code is available & stars >= 100 | โญ citation >= 50 | ๐ŸŽ“ Top-tier venue

kg.: Knowledge Graphโ€ƒ| data.: dataset โ€ƒ| โ€ƒ 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
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] [่งฃ่ฏป]
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] [่งฃ่ฏป]
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 โญ DZNE; University of Bonn; Nature ๐ŸŽ“ 2021 [PUB] [CODE] [SOFTWARE] [่งฃ่ฏป]
End-to-end privacy preserving deep learning on multi-institutional medical imaging TUM; Imperial College London; OpenMined Nat. Mach. Intell. 2021 [PUB] [CODE] [่งฃ่ฏป]
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 โญ 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
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] [่งฃ่ฏป]
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 IJCAI 2023 [PDF]
HyperFed: Hyperbolic Prototypes Exploration with Consistent Aggregation for Non-IID Data in Federated Learning IJCAI 2023
FedOBD: Opportunistic Block Dropout for Efficiently Training Large-scale Neural Networks through Federated Learning IJCAI 2023 [PDF] [CODE]
Federated Probabilistic Preference Distribution Modelling with Compactness Co-Clustering for Privacy-Preserving Multi-Domain Recommendation IJCAI 2023
Federated Graph Semantic and Structural Learning IJCAI 2023
BARA: Efficient Incentive Mechanism with Online Reward Budget Allocation in Cross-Silo Federated Learning IJCAI 2023 [PDF]
FedDWA: Personalized Federated Learning with Dynamic Weight Adjustment IJCAI 2023 [PDF]
FedPass: Privacy-Preserving Vertical Federated Deep Learning with Adaptive Obfuscation IJCAI 2023 [PDF]
Globally Consistent Federated Graph Autoencoder for Non-IID Graphs IJCAI 2023
Competitive-Cooperative Multi-Agent Reinforcement Learning for Auction-based Federated Learning IJCAI 2023
Dual Personalization on Federated Recommendation IJCAI 2023 [PDF] [CODE]
FedNoRo: Towards Noise-Robust Federated Learning by Addressing Class Imbalance and Label Noise Heterogeneity IJCAI 2023 [PDF] [CODE]
Denial-of-Service or Fine-Grained Control: Towards Flexible Model Poisoning Attacks on Federated Learning IJCAI 2023 [PDF] [CODE]
FedHGN: A Federated Framework for Heterogeneous Graph Neural Networks IJCAI 2023 [PDF] [CODE]
FedET: A Communication-Efficient Federated Class-Incremental Learning Framework Based on Enhanced Transformer IJCAI 2023 [PDF]
Prompt Federated Learning for Weather Forecasting: Toward Foundation Models on Meteorological Data IJCAI 2023 [PDF] [CODE]
FedBFPT: An Efficient Federated Learning Framework for Bert Further Pre-training IJCAI 2023
Bayesian Federated Learning: A Survey IJCAI Survey Track 2023 [PDF]
A Survey of Federated Evaluation in Federated Learning IJCAI Survey Track 2023 [PDF]
SAMBA: A Generic Framework for Secure Federated Multi-Armed Bandits (Extended Abstract) IJCAI Journal Track 2023
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 ฬ e Cห† ote dโ€™Azur AISTATS 2023 [PUB] [CODE]
Nothing but Regrets โ€” 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] [่งฃ่ฏป]
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] [่งฃ่ฏป]
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. ๐Ÿ”ฅ 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] [่งฃ่ฏป]
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 ๐Ÿ”ฅ 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] [่งฃ่ฏป]
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 ๐Ÿ”ฅ 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).

fl in top ml conference and journal
Title Affiliation Venue Year Materials
Dynamic Regularized Sharpness Aware Minimization in Federated Learning: Approaching Global Consistency and Smooth Landscape ICML 2023 [PUB]
Analysis of Error Feedback in Federated Non-Convex Optimization with Biased Compression: Fast Convergence and Partial Participation ICML 2023 [PUB]
FedHPO-Bench: A Benchmark Suite for Federated Hyperparameter Optimization ICML 2023 [PUB]
Federated Conformal Predictors for Distributed Uncertainty Quantification ICML 2023 [PUB] [CODE]
Federated Adversarial Learning: A Framework with Convergence Analysis ICML 2023 [PUB]
Federated Heavy Hitter Recovery under Linear Sketching ICML 2023 [PUB]
Doubly Adversarial Federated Bandits ICML 2023 [PUB]
Achieving Linear Speedup in Non-IID Federated Bilevel Learning ICML 2023 [PUB]
One-Shot Federated Conformal Prediction ICML 2023 [PUB]
Federated Online and Bandit Convex Optimization ICML 2023 [PUB]
Federated Linear Contextual Bandits with User-level Differential Privacy ICML 2023 [PUB]
Vertical Federated Graph Neural Network for Recommender System ICML 2023 [PUB] [CODE]
Communication-Efficient Federated Hypergradient Computation via Aggregated Iterative Differentiation ICML 2023 [PUB]
Towards Understanding Ensemble Distillation in Federated Learning ICML 2023 [PUB]
Personalized Subgraph Federated Learning ICML 2023 [PUB]
Conformal Prediction for Federated Uncertainty Quantification Under Label Shift ICML 2023 [PUB]
Secure Federated Correlation Test and Entropy Estimation ICML 2023 [PUB]
Out-of-Distribution Generalization of Federated Learning via Implicit Invariant Relationships ICML 2023 [PUB]
Personalized Federated Learning under Mixture of Distributions ICML 2023 [PUB]
FedDisco: Federated Learning with Discrepancy-Aware Collaboration ICML 2023 [PUB]
Anchor Sampling for Federated Learning with Partial Client Participation ICML 2023 [PUB] [CODE]
Private Federated Learning with Autotuned Compression ICML 2023 [PUB]
Fast Federated Machine Unlearning with Nonlinear Functional Theory ICML 2023 [PUB]
On the Convergence of Federated Averaging with Cyclic Client Participation ICML 2023 [PUB]
Revisiting Weighted Aggregation in Federated Learning with Neural Networks ICML 2023 [PUB] [CODE]
The Blessing of Heterogeneity in Federated Q-Learning: Linear Speedup and Beyond ICML 2023 [PUB]
GuardHFL: Privacy Guardian for Heterogeneous Federated Learning ICML 2023 [PUB]
Flash: Concept Drift Adaptation in Federated Learning ICML 2023 [PUB]
DoCoFL: Downlink Compression for Cross-Device Federated Learning ICML 2023 [PUB]
FeDXL: Provable Federated Learning for Deep X-Risk Optimization ICML 2023 [PUB] [CODE]
No One Idles: Efficient Heterogeneous Federated Learning with Parallel Edge and Server Computation ICML 2023 [PUB]
Personalized Federated Learning with Inferred Collaboration Graphs ICML 2023 [PUB]
Optimizing the Collaboration Structure in Cross-Silo Federated Learning ICML 2023 [PUB] [CODE]
TabLeak: Tabular Data Leakage in Federated Learning ICML 2023 [PUB]
FedCR: Personalized Federated Learning Based on Across-Client Common Representation with Conditional Mutual Information Regularization ICML 2023 [PUB]
Fed-CBS: A Heterogeneity-Aware Client Sampling Mechanism for Federated Learning via Class-Imbalance Reduction ICML 2023 [PUB]
Privacy-Aware Compression for Federated Learning Through Numerical Mechanism Design ICML 2023 [PUB]
SRATTA: Sample Re-ATTribution Attack of Secure Aggregation in Federated Learning ICML 2023 [PUB]
Improving the Model Consistency of Decentralized Federated Learning ICML 2023 [PUB]
Efficient Personalized Federated Learning via Sparse Model-Adaptation ICML 2023 [PUB] [CODE]
From Noisy Fixed-Point Iterations to Private ADMM for Centralized and Federated Learning ICML 2023 [PUB]
LeadFL: Client Self-Defense against Model Poisoning in Federated Learning ICML 2023 [PUB]
Chameleon: Adapting to Peer Images for Planting Durable Backdoors in Federated Learning ICML 2023 [PUB] [CODE]
FedVS: Straggler-Resilient and Privacy-Preserving Vertical Federated Learning for Split Models ICML 2023 [PUB]
FedBR: Improving Federated Learning on Heterogeneous Data via Local Learning Bias Reduction ICML 2023 [PUB] [CODE]
Towards Unbiased Training in Federated Open-world Semi-supervised Learning ICML 2023 [PUB]
Cocktail Party Attack: Breaking Aggregation-Based Privacy in Federated Learning Using Independent Component Analysis ICML 2023 [PUB]
Surrogate Model Extension (SME): A Fast and Accurate Weight Update Attack on Federated Learning ICML 2023 [PUB] [CODE]
Fair yet Asymptotically Equal Collaborative Learning ICML 2023 [PUB]
Sketching for First Order Method: Efficient Algorithm for Low-Bandwidth Channel and Vulnerability ICML 2023 [PUB]
Adversarial Collaborative Learning on Non-IID Features ICML 2023 [PUB]
XTab: Cross-table Pretraining for Tabular Transformers ICML 2023 [PUB]
Momentum Ensures Convergence of SIGNSGD under Weaker Assumptions ICML 2023 [PUB]
Byzantine-Robust Learning on Heterogeneous Data via Gradient Splitting ICML 2023 [PUB]
LESS-VFL: Communication-Efficient Feature Selection for Vertical Federated Learning ICML 2023 [PUB]
FedAvg Converges to Zero Training Loss Linearly for Overparameterized Multi-Layer Neural Networks ICML 2023 [PUB]
Addressing Budget Allocation and Revenue Allocation in Data Market Environments Using an Adaptive Sampling Algorithm ICML 2023 [PUB]
Robust federated learning under statistical heterogeneity via hessian-weighted aggregation Deakin University Mach Learn 2023 [PUB]
FedLab: A Flexible Federated Learning Framework ๐Ÿ”ฅ 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 ฬe Cห† ote dโ€™Azur JMLR 2023 [PUB] [PDF] [CODE]
FedIPR: Ownership Verification for Federated Deep Neural Network Models SJTU TPAMI 2023 [PUB] [PDF] [CODE] [่งฃ่ฏป]
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 Universitรฉ 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(ฯตโˆ’2) Communication Complexity in Federated Min-Max Learning OSU NeurIPS 2022 [PUB] [PDF]
Taming Fat-Tailed (โ€œHeavier-Tailedโ€ 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 ๐Ÿ”ฅ 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 ๐Ÿ”ฅ 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] [่งฃ่ฏป]
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] [่งฃ่ฏป]
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 ๐Ÿ”ฅ 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 ๐Ÿ”ฅ 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 ๐Ÿ”ฅ 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? ๐Ÿ”ฅ 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] [่งฃ่ฏป]
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 ๐Ÿ”ฅ CMU; Google ICLR 2021 [PUB] [PDF] [CODE]
Adaptive Federated Optimization ๐Ÿ”ฅ 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 ๐Ÿ”ฅ 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] [่งฃ่ฏป]
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 ๐Ÿ”ฅ Bar-Ilan University; NVIDIA ICML 2021 [PUB] [PDF] [CODE] [PAGE] [VIDEO] [่งฃ่ฏป]
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 ๐Ÿ”ฅ 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 ๐Ÿ”ฅ 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] [่งฃ่ฏป]
The Skellam Mechanism for Differentially Private Federated Learning ๐Ÿ”ฅ 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] [่งฃ่ฏป]
Evaluating Gradient Inversion Attacks and Defenses in Federated Learning ๐Ÿ”ฅ 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 ๐Ÿ”ฅ 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] [่งฃ่ฏป]
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 ๐Ÿ”ฅ 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 โ€“ 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 ๐Ÿ”ฅ CMU; Facebook AI ICLR 2020 [PUB] [PDF] [CODE]
Federated Learning with Matched Averaging ๐Ÿ”ฅ 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 ๐Ÿ”ฅ Google ICLR 2020 [PUB] [PDF] [CODE]
On the Convergence of FedAvg on Non-IID Data ๐Ÿ”ฅ PKU ICLR 2020 [PUB] [PDF] [CODE] [่งฃ่ฏป]
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.] [่งฃ่ฏป]
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 ๐Ÿ”ฅ Pennsylvania State University NeurIPS 2020 [PUB] [PDF] [CODE]
Personalized Federated Learning with Moreau Envelopes ๐Ÿ”ฅ 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] [่งฃ่ฏป]
Tackling the Objective Inconsistency Problem in Heterogeneous Federated Optimization ๐Ÿ”ฅ 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? ๐Ÿ”ฅ 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 ๐Ÿ”ฅ IBM ICML 2019 [PUB] [PDF] [CODE]
Analyzing Federated Learning through an Adversarial Lens ๐Ÿ”ฅ 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 ๐Ÿ”ฅ 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).

fl in top dm conference and journal
Title Affiliation Venue Year Materials
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 ๐Ÿ”ฅ 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] [่งฃ่ฏป]
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] [่งฃ่ฏป]
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 Zรผrich 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
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]
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]
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]
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 Universitรฉ du Quรฉbรฉc รก Montrรฉal S&P ๏ผˆWorkshop๏ผ‰ 2019 [PUB]
Comprehensive Privacy Analysis of Deep Learning: Passive and Active White-box Inference Attacks against Centralized and Federated Learning ๐Ÿ”ฅ University of Massachusetts Amherst S&P 2019 [PUB] [VIDEO] [SLIDE] [CODE]
Practical Secure Aggregation for Privacy Preserving Machine Learning Google CCS 2017 [PUB] [PDF] [่งฃ่ฏป] [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
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]
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] [่งฃ่ฏป]
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]
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 ๐Ÿ”ฅ NUS; UC Berkeley CVPR 2021 [PUB] [PDF] [CODE] [่งฃ่ฏป]
FedDG: Federated Domain Generalization on Medical Image Segmentation via Episodic Learning in Continuous Frequency Space ๐Ÿ”ฅ 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] [่งฃ่ฏป]

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 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]
Dim-Krum: Backdoor-Resistant Federated Learning for NLP with Dimension-wise Krum-Based Aggregation PKU EMNLP 2022 [PUB] [PDF]
Efficient Federated Learning on Knowledge Graphs via Privacy-preserving Relation Embedding Aggregation kg. Lehigh University EMNLP 2022 [PUB] [PDF] [CODE]
Federated Continual Learning for Text Classification via Selective Inter-client Transfer DRIMCo GmbH; LMU EMNLP 2022 [PUB] [PDF] [CODE]
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]
Federated Meta-Learning for Emotion and Sentiment Aware Multi-modal Complaint Identification EMNLP 2022 [PUB]
Fair NLP Models with Differentially Private Text Encoders EMNLP 2022 [PUB] [PDF] [CODE]
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 ๐Ÿ”ฅ 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]
Training Mixed-Domain Translation Models via Federated Learning Amazon NAACL 2022 [PUB] [PAGE] [PDF]
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 Universitรคt 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] [่งฃ่ฏป]
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 Childrenโ€™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).

fl in top ir conference and journal
Title Affiliation Venue Year Materials
Personalized Federated Relation Classification over Heterogeneous Texts SIGIR 2023
Fine-Grained Preference-Aware Personalized Federated POI Recommendation with Data Sparsity SIGIR 2023
Manipulating Federated Recommender Systems: Poisoning with Synthetic Users and Its Countermeasures SIGIR 2023
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
Differentially Private Vertical Federated Clustering. Purdue University VLDB 2023 [PUB] [PDF] [CODE]
FederatedScope: A Flexible Federated Learning Platform for Heterogeneity. ๐Ÿ”ฅ 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. ๐Ÿ”ฅ 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).

fl in top network conference and journal
Title Affiliation Venue Year Materials
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
A Reinforcement Learning Approach for Minimizing Job Completion Time in Clustered Federated Learning Southeast University INFOCOM 2023
Adaptive Configuration for Heterogeneous Participants in Decentralized Federated Learning USTC INFOCOM 2023 [PDF]
AnycostFL: Efficient On-Demand Federated Learning over Heterogeneous Edge Devices Guangdong University of Technology INFOCOM 2023 [PDF]
AOCC-FL: Federated Learning with Aligned Overlapping via Calibrated Compensation HUST INFOCOM 2023
Asynchronous Federated Unlearning University of Toronto INFOCOM 2023 [PDF]
Communication-Efficient Federated Learning for Heterogeneous Edge Devices Based on Adaptive Gradient Quantization PSU INFOCOM 2023 [PDF]
Enabling Communication-Efficient Federated Learning via Distributed Compressed Sensing Beihang University INFOCOM 2023
Federated Learning under Heterogeneous and Correlated Client Availability Inria INFOCOM 2023 [PDF] [CODE]
Federated Learning with Flexible Control IBM INFOCOM 2023 [PDF]
Federated PCA on Grassmann Manifold for Anomaly Detection in IoT Networks The University of Sydney INFOCOM 2023 [PDF]
FedMoS: Taming Client Drift in Federated Learning with Double Momentum and Adaptive Selection HUST INFOCOM 2023 [PDF]
FedSDG-FS: Efficient and Secure Feature Selection for Vertical Federated Learning NTU INFOCOM 2023
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
Joint Participation Incentive and Network Pricing Design for Federated Learning Northwestern University INFOCOM 2023
More than Enough is Too Much: Adaptive Defenses against Gradient Leakage in Production Federated Learning University of Toronto INFOCOM 2023 [PDF]
Network Adaptive Federated Learning: Congestion and Lossy Compression UTAustin INFOCOM 2023 [PDF]
OBLIVION: Poisoning Federated Learning by Inducing Catastrophic Forgetting The Hang Seng University of Hong Kong INFOCOM 2023
Privacy as a Resource in Differentially Private Federated Learning BUPT INFOCOM 2023
SplitGP: Achieving Both Generalization and Personalization in Federated Learning KAIST INFOCOM 2023 [PDF]
SVDFed: Enabling Communication-Efficient Federated Learning via Singular-Value-Decomposition Beihang University INFOCOM 2023
Tackling System Induced Bias in Federated Learning: Stratification and Convergence Analysis Southern University of Science and Technology INFOCOM 2023 [PDF]
Toward Sustainable AI: Federated Learning Demand Response in Cloud-Edge Systems via Auctions BUPT INFOCOM 2023 [PDF]
Truthful Incentive Mechanism for Federated Learning with Crowdsourced Data Labeling Auburn University INFOCOM 2023 [PDF]
TVFL: Tunable Vertical Federated Learning towards Communication-Efficient Model Serving USTC INFOCOM 2023
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 ๐Ÿ”ฅ University of Toronto INFOCOM 2020 [PUB] [SLIDE] [CODE] [่งฃ่ฏป]
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), 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).

fl in top system conference and journal
Title Affiliation Venue Year Materials
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]
Optimizing Training Efficiency and Cost of Hierarchical Federated Learning in Heterogeneous Mobile-Edge Cloud Computing ECNU TCAD 2023 [PUB]
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]
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. TPDS 2023 [PUB] [PDF]
From Deterioration to Acceleration: A Calibration Approach to Rehabilitating Step Asynchronism in Federated Optimization. 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]
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] [่งฃ่ฏป]
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]
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] [่งฃ่ฏป]
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 ๐Ÿ”ฅ University of Michigan SOSP workshop / ICML 2022 2021 [PUB] [PDF] [CODE] [่งฃ่ฏป]
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]
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 ๐Ÿ”ฅ CMU MLSys 2020 [PUB] [PDF] [CODE]
Towards Federated Learning at Scale: System Design Google MLSys 2019 [PUB] [PDF] [่งฃ่ฏป]

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).

fl in top conference and journal other fields
Title Affiliation Venue Year TL;DR Materials

fl on graph data and graph neural networks

dblp

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
Federated Visualization: A Privacy-Preserving Strategy for Aggregated Visual Query. ZJU IEEE Trans. Vis. Comput. Graph. ๐ŸŽ“ 2023 [PUB] [PDF]
Personalized Subgraph Federated Learning KAIST ICML ๐ŸŽ“ 2023 [PDF]
Semi-decentralized Federated Ego Graph Learning for Recommendation SUST WWW๐ŸŽ“ 2023 [PUB] [PDF]
Federated Graph Neural Network for Fast Anomaly Detection in Controller Area Networks ECUST IEEE Trans. Inf. Forensics Secur. ๐ŸŽ“ 2023 [PUB]
Federated Learning Over Coupled Graphs XJTU IEEE Trans. Parallel Distributed Syst. ๐ŸŽ“ 2023 [PUB] [PDF]
HetVis: A Visual Analysis Approach for Identifying Data Heterogeneity in Horizontal Federated Learning Nankai University IEEE Trans. Vis. Comput. Graph. ๐ŸŽ“ 2023 [PUB] [PDF]
Federated Learning on Non-IID Graphs via Structural Knowledge Sharing UTS AAAI ๐ŸŽ“ 2023 [PDF] [CODE]
FedGS: Federated Graph-based Sampling with Arbitrary Client Availability XMU AAAI ๐ŸŽ“ 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]
FedWalk: Communication Efficient Federated Unsupervised Node Embedding with Differential Privacy SJTU KDD ๐ŸŽ“ 2022 [PUB] [PDF]
FederatedScope-GNN: Towards a Unified, Comprehensive and Efficient Platform for Federated Graph Learning ๐Ÿ”ฅ Alibaba KDD (Best Paper Award) ๐ŸŽ“ 2022 [PDF] [CODE] [PUB]
Deep Neural Network Fusion via Graph Matching with Applications to Model Ensemble and Federated Learning SJTU ICML ๐ŸŽ“ 2022 [PUB] [CODE]
Meta-Learning Based Knowledge Extrapolation for Knowledge Graphs in the Federated Setting kg. ZJU IJCAI ๐ŸŽ“ 2022 [PUB] [PDF] [CODE]
Personalized Federated Learning With a Graph UTS IJCAI ๐ŸŽ“ 2022 [PUB] [PDF] [CODE]
Vertically Federated Graph Neural Network for Privacy-Preserving Node Classification ZJU IJCAI ๐ŸŽ“ 2022 [PUB] [PDF]
SpreadGNN: Decentralized Multi-Task Federated Learning for Graph Neural Networks on Molecular Data USC AAAI๐ŸŽ“ 2022 [PUB] [PDF] [CODE] [่งฃ่ฏป]
FedGraph: Federated Graph Learning with Intelligent Sampling UoA TPDS ๐ŸŽ“ 2022 [PUB] [CODE] [่งฃ่ฏป]
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] [่งฃ่ฏป]
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] [่งฃ่ฏป]
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]
FedGCN: Convergence and Communication Tradeoffs in Federated Training of Graph Convolutional Networks CMU CIKM Workshop (Oral) 2022 [PDF] [CODE]
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] [่งฃ่ฏป]
Device Sampling for Heterogeneous Federated Learning: Theory, Algorithms, and Implementation. Purdue INFOCOM ๐ŸŽ“ 2021 [PUB] [PDF]
Federated Graph Classification over Non-IID Graphs Emory NeurIPS ๐ŸŽ“ 2021 [PUB] [PDF] [CODE] [่งฃ่ฏป]
Subgraph Federated Learning with Missing Neighbor Generation Emory; UBC; Lehigh University NeurIPS ๐ŸŽ“ 2021 [PUB] [PDF]
Cross-Node Federated Graph Neural Network for Spatio-Temporal Data Modeling USC KDD ๐ŸŽ“ 2021 [PUB] [PDF] [CODE] [่งฃ่ฏป]
Differentially Private Federated Knowledge Graphs Embedding kg. BUAA CIKM 2021 [PUB] [PDF] [CODE] [่งฃ่ฏป]
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] [่งฃ่ฏป]
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 ๐Ÿ”ฅ surv. USC ICLR Workshop / MLSys Workshop 2021 [PDF] [CODE] [่งฃ่ฏป]
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] [่งฃ่ฏป]
FedGNN: Federated Graph Neural Network for Privacy-Preserving Recommendation THU ICML workshop 2021 [PDF] [่งฃ่ฏป]
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] [่งฃ่ฏป]
Decentralized federated learning for electronic health records UMN NeurIPS Workshop / CISS 2020 [PUB] [PDF] [่งฃ่ฏป]
ASFGNN: Automated Separated-Federated Graph Neural Network Ant Group PPNA 2020 [PUB] [PDF] [่งฃ่ฏป]
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 โญ 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] [่งฃ่ฏป]

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

dblp

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. ๐ŸŽ“ 2023 [PUB] [CODE]
Incentive-boosted Federated Crowdsourcing SDU AAAI ๐ŸŽ“ 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. ๐ŸŽ“ 2022 [PUB] [PDF] [CODE]
RevFRF: Enabling Cross-Domain Random Forest Training With Revocable Federated Learning XIDIAN UNIVERSITY IEEE Trans. Dependable Secur. Comput. ๐ŸŽ“ 2022 [PUB] [PDF]
A Tree-based Model Averaging Approach for Personalized Treatment Effect Estimation from Heterogeneous Data Sources University of Pittsburgh ICML ๐ŸŽ“ 2022 [PUB] [PDF] [CODE]
Federated Boosted Decision Trees with Differential Privacy University of Warwick CCS ๐ŸŽ“ 2022 [PUB] [PDF] [CODE]
Federated Functional Gradient Boosting University of Pennsylvania AISTATS ๐ŸŽ“ 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 Zรผrich 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 ๐ŸŽ“ 2021 [PUB]
Boosting with Multiple Sources Google NeurIPS๐ŸŽ“ 2021 [PUB]
SecureBoost: A Lossless Federated Learning Framework ๐Ÿ”ฅ UC IEEE Intell. Syst. 2021 [PUB] [PDF] [SLIDE] [CODE] [่งฃ่ฏป] [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 Umeรฅ 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 ๐ŸŽ“ 2020 [PUB] [PDF] [CODE]
Privacy Preserving Vertical Federated Learning for Tree-based Models NUS VLDB ๐ŸŽ“ 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] [่งฃ่ฏป]
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 ๐Ÿ”ฅ 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 SG ST Materials
PySyft
Stars
 A generic framework for privacy preserving deep learning OpenMined [DOC]
FATE
Stars
 FATE: An Industrial Grade Platform for Collaborative Learning With Data Protection WeBank โœ…โœ… [DOC] [DOC(ZH)]
MindSpore Federated
Stars
 HUAWEI [DOC] [PAGE]
FedML
Stars
 FedML: A Research Library and Benchmark for Federated Machine Learning FedML โœ…โœ… โœ… [DOC]
Flower
Stars
 Flower: A Friendly Federated Learning Research Framework flower.dev adap [DOC]
TFF(Tensorflow-Federated)
Stars
 Towards Federated Learning at Scale: System Design Google [DOC] [PAGE]
SecretFlow
Stars
 Ant group โœ… [DOC]
FederatedScope
Stars
 FederatedScope: A Flexible Federated Learning Platform for Heterogeneity Alibaba DAMO Academy โœ…โœ… [DOC] [PAGE]
Fedlearner
Stars
 Bytedance
LEAF
Stars
 LEAF: A Benchmark for Federated Settings CMU
PFL-Non-IID
Stars
 FedALA: Adaptive Local Aggregation for Personalized Federated Learning SJTU
OpenFL
Stars
 OpenFL: An open-source framework for Federated Learning Intel [DOC]
Rosetta
Stars
 matrixelements [DOC] [PAGE]
Fedlab
Stars
 FedLab: A Flexible Federated Learning Framework SMILELab [DOC] [DOC(ZH)] [PAGE]
PaddleFL
Stars
 Baidu [DOC]
IBM Federated Learning
Stars
 IBM Federated Learning: an Enterprise Framework White Paper IBM โœ… [PAPERS]
Primihub
Stars
 primihub [DOC]
Privacy Meter
Stars
 Comprehensive Privacy Analysis of Deep Learning: Passive and Active White-box Inference Attacks against Centralized and Federated Learning University of Massachusetts Amherst
NIID-Bench
Stars
 Federated Learning on Non-IID Data Silos: An Experimental Study Xtra Computing Group
KubeFATE
Stars
 WeBank [WIKI]
NVFlare
Stars
 NVIDIA [DOC]
Differentially Private Federated Learning: A Client-level Perspective
Stars
 Differentially Private Federated Learning: A Client Level Perspective SAP-samples
FedScale
Stars
 FedScale: Benchmarking Model and System Performance of Federated Learning at Scale SymbioticLab(U-M)
easyFL
Stars
 Federated Learning with Fair Averaging XMU
Backdoors 101
Stars
 Blind Backdoors in Deep Learning Models Cornell Tech
SWARM LEARNING
Stars
 Swarm Learning for decentralized and confidential clinical machine learning [VIDEO]
substra
Stars
 Substra [DOC]
FedJAX
Stars
 FEDJAX: Federated learning simulation with JAX Google
plato
Stars
 UofT
FedNLP
Stars
 FedNLP: Benchmarking Federated Learning Methods for Natural Language Processing Tasks FedML
Galaxy Federated Learning
Stars
 GFL: A Decentralized Federated Learning Framework Based On Blockchain ZJU [DOC]
Xaynet
Stars
 XayNet [PAGE] [DOC] [WHITEPAPER] [LEGAL REVIEW]
SyferText
Stars
 OpenMined
EasyFL
Stars
 EasyFL: A Low-code Federated Learning Platform For Dummies NTU
FLSim
Stars
 facebook research
Breaching
Stars
 A Framework for Attacks against Privacy in Federated Learning (papers)
FedGraphNN
Stars
 FedGraphNN: A Federated Learning System and Benchmark for Graph Neural Networks FedML โœ…โœ…
PyVertical
Stars
 PyVertical: A Vertical Federated Learning Framework for Multi-headed SplitNN OpenMined
FLUTE
Stars
 FLUTE: A Scalable, Extensible Framework for High-Performance Federated Learning Simulations microsoft [DOC]
FedTorch
Stars
 Distributionally Robust Federated Averaging Penn State
FLSim
Stars
 Optimizing Federated Learning on Non-IID Data with Reinforcement Learning University of Toronto
PhotoLabeller
Stars
 [BLOG]
FATE-Serving
Stars
 WeBank [DOC]
PriMIA
Stars
 End-to-end privacy preserving deep learning on multi-institutional medical imaging TUM; Imperial College London; OpenMined [DOC]
9nfl
Stars
 JD
FedTree
Stars
 FedTree: A Federated Learning System For Trees Xtra Computing Group โœ…โœ… [DOC]
FEDn
Stars
 Scalable federated machine learning with FEDn scaleoutsystems [DOC]
FedLearn
Stars
 Fedlearn-Algo: A flexible open-source privacy-preserving machine learning platform JD
FedCV
Stars
 FedCV: A Federated Learning Framework for Diverse Computer Vision Tasks FedML
FeTS
Stars
 The federated tumor segmentation (FeTS) tool: an open-source solution to further solid tumor research Federated Tumor Segmentation (FeTS) initiative [DOC]
MPLC
Stars
 LabeliaLabs [PAGE]
UCADI
Stars
 Advancing COVID-19 diagnosis with privacy-preserving collaboration in artificial intelligence Huazhong University of Science and Technology
Flame
Stars
 Cisco [DOC]
APPFL
Stars
 [DOC]
FlexCFL
Stars
 Flexible Clustered Federated Learning for Client-Level Data Distribution Shift Chongqing University
OpenFed
Stars
 OpenFed: A Comprehensive and Versatile Open-Source Federated Learning Framework [DOC]
FedGroup
Stars
 FedGroup: Efficient Clustered Federated Learning via Decomposed Data-Driven Measure Chongqing University
FedEval
Stars
 FedEval: A Benchmark System with a Comprehensive Evaluation Model for Federated Learning HKU [DOC]
FedSim
Stars
Federated-Learning-source
Stars
 A Practical Federated Learning Framework for Small Number of Stakeholders ETH Zรผrich [DOC]
Clara NVIDIA
OpenHealth
Stars
 ZJU

benchmark

  • UniFed leaderboard

Here's a really great Benchmark for the federated learning open source framework ๐Ÿ‘ 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

graph datasets

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)

  • [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

course

secret sharing

key conferences/workshops/journals

This section partially refers to The Federated Learning Portal.

workshops

  • [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-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

conference special tracks

update log

  • 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". ๐Ÿ“ˆ
  • 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. ๐Ÿ˜ƒ
  • 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(่งฃ่ฏป) 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-catโ€˜s Awesome-Federated-Machine-Learning and find ๐Ÿ”ฅ 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 โค๏ธ 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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