Federated Learning
Decentralized learning across devices
Top Papers
FedDAT: An Approach for Foundation Model Finetuning in Multi-Modal Heterogeneous Federated Learning
Haokun Chen, Yao Zhang, Denis Krompass et al.
FedASMU: Efficient Asynchronous Federated Learning with Dynamic Staleness-Aware Model Update
Ji Liu, Juncheng Jia, Tianshi Che et al.
FedAS: Bridging Inconsistency in Personalized Federated Learning
Xiyuan Yang, Wenke Huang, Mang Ye
Fair Federated Learning under Domain Skew with Local Consistency and Domain Diversity
Yuhang Chen, Wenke Huang, Mang Ye
Selective Aggregation for Low-Rank Adaptation in Federated Learning
Pengxin Guo, Shuang Zeng, Yanran Wang et al.
Federated Adaptive Prompt Tuning for Multi-Domain Collaborative Learning
Shangchao Su, Mingzhao Yang, Bin Li et al.
Communication-Efficient Federated Learning with Accelerated Client Gradient
Geeho Kim, Jinkyu Kim, Bohyung Han
Towards Efficient Replay in Federated Incremental Learning
Yichen Li, Qunwei Li, Haozhao Wang et al.
FedSelect: Personalized Federated Learning with Customized Selection of Parameters for Fine-Tuning
Rishub Tamirisa, Chulin Xie, Wenxuan Bao et al.
Exploiting Label Skews in Federated Learning with Model Concatenation
Yiqun Diao, Qinbin Li, Bingsheng He
Finite-Time Analysis of On-Policy Heterogeneous Federated Reinforcement Learning
Chenyu Zhang, Han Wang, Aritra Mitra et al.
Fair and Efficient Contribution Valuation for Vertical Federated Learning
Zhenan Fan, Huang Fang, Xinglu Wang et al.
Personalized Federated Domain-Incremental Learning based on Adaptive Knowledge Matching
Yichen Li, Wenchao Xu, Haozhao Wang et al.
Backdoor Federated Learning by Poisoning Backdoor-Critical Layers
Haomin Zhuang, Mingxian Yu, Hao Wang et al.
Asynchronous Federated Reinforcement Learning with Policy Gradient Updates: Algorithm Design and Convergence Analysis
Guangchen (Eric) Lan, Dong-Jun Han, Abolfazl Hashemi et al.
Unlocking the Potential of Prompt-Tuning in Bridging Generalized and Personalized Federated Learning
wenlong deng, Christos Thrampoulidis, Xiaoxiao Li
Improving Plasticity in Online Continual Learning via Collaborative Learning
Maorong Wang, Nicolas Michel, Ling Xiao et al.
PerAda: Parameter-Efficient Federated Learning Personalization with Generalization Guarantees
Chulin Xie, De-An Huang, Wenda Chu et al.
An Upload-Efficient Scheme for Transferring Knowledge From a Server-Side Pre-trained Generator to Clients in Heterogeneous Federated Learning
Jianqing Zhang, Yang Liu, Yang Hua et al.
Federated Learning with Extremely Noisy Clients via Negative Distillation
Yang Lu, Lin Chen, Yonggang Zhang et al.
FedFixer: Mitigating Heterogeneous Label Noise in Federated Learning
Xinyuan Ji, Zhaowei Zhu, Wei Xi et al.
Federated Q-Learning: Linear Regret Speedup with Low Communication Cost
Zhong Zheng, Fengyu Gao, Lingzhou Xue et al.
Mixed-Precision Quantization for Federated Learning on Resource-Constrained Heterogeneous Devices
Huancheng Chen, Haris Vikalo
Diffusion-Driven Data Replay: A Novel Approach to Combat Forgetting in Federated Class Continual Learning
Jinglin Liang, Jin Zhong, Hanlin Gu et al.
PILoRA: Prototype Guided Incremental LoRA for Federated Class-Incremental Learning
Haiyang Guo, Fei Zhu, Wenzhuo Liu et al.
Cloud-Device Collaborative Learning for Multimodal Large Language Models
Guanqun Wang, Jiaming Liu, Chenxuan Li et al.
Text-Enhanced Data-free Approach for Federated Class-Incremental Learning
Minh-Tuan Tran, Trung Le, Xuan-May Le et al.
Benchmarking Algorithms for Federated Domain Generalization
Ruqi Bai, Saurabh Bagchi, David Inouye
Data Valuation and Detections in Federated Learning
Wenqian Li, Shuran Fu, Fengrui Zhang et al.
Efficiently Assemble Normalization Layers and Regularization for Federated Domain Generalization
Khiem Le, Tuan Long Ho, Cuong Do et al.
Combating Data Imbalances in Federated Semi-supervised Learning with Dual Regulators
Sikai Bai, Shuaicheng Li, Weiming Zhuang et al.
Federated Unlearning with Gradient Descent and Conflict Mitigation
Zibin Pan, Zhichao Wang, Chi Li et al.
Towards Fair Graph Federated Learning via Incentive Mechanisms
12794 Chenglu Pan, Jiarong Xu, Yue Yu et al.
Fed-QSSL: A Framework for Personalized Federated Learning under Bitwidth and Data Heterogeneity
Yiyue Chen, Haris Vikalo, Chianing Wang
FedLoGe: Joint Local and Generic Federated Learning under Long-tailed Data
Zikai Xiao, Zihan Chen, Liyinglan Liu et al.
Performative Federated Learning: A Solution to Model-Dependent and Heterogeneous Distribution Shifts
Kun Jin, Tongxin Yin, Zhongzhu Chen et al.
BAFFLE: A Baseline of Backpropagation-Free Federated Learning
Haozhe Feng, Tianyu Pang, Chao Du et al.
NoT: Federated Unlearning via Weight Negation
Yasser Khalil, Leo Maxime Brunswic, Soufiane Lamghari et al.
Knowledge-Aware Parameter Coaching for Personalized Federated Learning
Mingjian Zhi, Yuanguo Bi, Wenchao Xu et al.
Federated Learning with Sample-level Client Drift Mitigation
Haoran Xu, Jiaze Li, Wanyi Wu et al.
FedLF: Layer-Wise Fair Federated Learning
Zibin Pan, Chi Li, Fangchen Yu et al.
FedLPS: Heterogeneous Federated Learning for Multiple Tasks with Local Parameter Sharing
Yongzhe Jia, Xuyun Zhang, Amin Beheshti et al.
FedMIA: An Effective Membership Inference Attack Exploiting "All for One" Principle in Federated Learning
Gongxi Zhu, Donghao Li, Hanlin Gu et al.
Energy-based Backdoor Defense Against Federated Graph Learning
Guancheng Wan, Zitong Shi, Wenke Huang et al.
Multi-Dimensional Fair Federated Learning
Cong Su, Guoxian Yu, Jun Wang et al.
A Primal-Dual Algorithm for Hybrid Federated Learning
Tom Overman, Garrett Blum, Diego Klabjan
LoCoDL: Communication-Efficient Distributed Learning with Local Training and Compression
Laurent Condat, Artavazd Maranjyan, Peter Richtarik
Learning Personalized Causally Invariant Representations for Heterogeneous Federated Clients
Xueyang Tang, Song Guo, Jie ZHANG et al.
AFL: A Single-Round Analytic Approach for Federated Learning with Pre-trained Models
Run He, Kai Tong, Di Fang et al.
Data Disparity and Temporal Unavailability Aware Asynchronous Federated Learning for Predictive Maintenance on Transportation Fleets
Leonie von Wahl, Niklas Heidenreich, Prasenjit Mitra et al.
Robust Training of Federated Models with Extremely Label Deficiency
Yonggang Zhang, Zhiqin Yang, Xinmei Tian et al.
FedCompetitors: Harmonious Collaboration in Federated Learning with Competing Participants
Shanli Tan, Hao Cheng, Xiaohu Wu et al.
FedTMOS: Efficient One-Shot Federated Learning with Tsetlin Machine
Shannon How, Jagmohan Chauhan, Geoff Merrett et al.
Multi-View Collaborative Learning Network for Speech Deepfake Detection
Kuiyuan Zhang, Zhongyun Hua, Rushi Lan et al.
Federated Partial Label Learning with Local-Adaptive Augmentation and Regularization
Yan Yan, Yuhong Guo
FedSA: A Unified Representation Learning via Semantic Anchors for Prototype-based Federated Learning
Yanbing Zhou, Xiangmou Qu, Chenlong You et al.
SuperFedNAS: Cost-Efficient Federated Neural Architecture Search for On-Device Inference
Alind Khare, Animesh Agrawal, Aditya Annavajjala et al.
Differentially Private Federated Learning with Time-Adaptive Privacy Spending
Shahrzad Kianidehkordi, Nupur Kulkarni, Adam Dziedzic et al.
Privacy-Preserving Personalized Federated Prompt Learning for Multimodal Large Language Models
Linh Tran, Wei Sun, Stacy Patterson et al.
Multiplayer Federated Learning: Reaching Equilibrium with Less Communication
TaeHo Yoon, Sayantan Choudhury, Nicolas Loizou
Towards Trustworthy Federated Learning with Untrusted Participants
Youssef Allouah, Rachid Guerraoui, John Stephan
On-Device Collaborative Language Modeling via a Mixture of Generalists and Specialists
Dongyang Fan, Bettina Messmer, Nikita Doikov et al.
PFedEdit: Personalized Federated Learning via Automated Model Editing
Haolin Yuan, William Paul, John Aucott et al.
dFLMoE: Decentralized Federated Learning via Mixture of Experts for Medical Data Analysis
Luyuan Xie, Tianyu Luan, Wenyuan Cai et al.
FedTSA: A Cluster-based Two-Stage Aggregation Method for Model-heterogeneous Federated Learning
Boyu Fan, Chenrui Wu, Xiang Su et al.
Decentralized Federated Learning with Model Caching on Mobile Agents
Xiaoyu Wang, Guojun Xiong, Houwei Cao et al.
Decoupled Training: Return of Frustratingly Easy Multi-Domain Learning
Ximei Wang, Junwei Pan, Xingzhuo Guo et al.
Unlocking the Potential of Model Calibration in Federated Learning
Yun-Wei Chu, Dong-Jun Han, Seyyedali Hosseinalipour et al.
Subgraph Federated Learning for Local Generalization
Sungwon Kim, Yoonho Lee, Yunhak Oh et al.
Towards Robust Parameter-Efficient Fine-Tuning for Federated Learning
Xiuwen Fang, Mang Ye
FlowerTune: A Cross-Domain Benchmark for Federated Fine-Tuning of Large Language Models
Yan Gao, Massimo R. Scamarcia, Javier Fernandez-Marques et al.
FedCALM: Conflict-aware Layer-wise Mitigation for Selective Aggregation in Deeper Personalized Federated Learning
Hao Zheng, Zhigang Hu, Boyu Wang et al.
Forgetting Through Transforming: Enabling Federated Unlearning via Class-Aware Representation Transformation
Qi Guo, Zhen Tian, Minghao Yao et al.
Ferret: Federated Full-Parameter Tuning at Scale for Large Language Models
Yao Shu, Wenyang Hu, See-Kiong Ng et al.
Leak and Learn: An Attacker's Cookbook to Train Using Leaked Data from Federated Learning
Joshua C. Zhao, Ahaan Dabholkar, Atul Sharma et al.
First-Order Federated Bilevel Learning
Yifan Yang, Peiyao Xiao, Shiqian Ma et al.
Watch Your Head: Assembling Projection Heads to Save the Reliability of Federated Models
Authors: Jinqian Chen, Jihua Zhu, Qinghai Zheng et al.
Exploit Gradient Skewness to Circumvent Byzantine Defenses for Federated Learning
Yuchen Liu, Chen Chen, Lingjuan Lyu et al.
GAS: Generative Activation-Aided Asynchronous Split Federated Learning
Jiarong Yang, Yuan Liu
FedLWS: Federated Learning with Adaptive Layer-wise Weight Shrinking
Changlong Shi, Jinmeng Li, He Zhao et al.
On the Byzantine-Resilience of Distillation-Based Federated Learning
Christophe Roux, Max Zimmer, Sebastian Pokutta
Query-based Knowledge Transfer for Heterogeneous Learning Environments
Norah Alballa, Wenxuan Zhang, Ziquan Liu et al.
SemiDFL: A Semi-Supervised Paradigm for Decentralized Federated Learning
Xinyang Liu, Pengchao Han, Xuan Li et al.
EBS-CFL: Efficient and Byzantine-robust Secure Clustered Federated Learning
Zhiqiang Li, Haiyong Bao, Menghong Guan et al.
Tackling Intertwined Data and Device Heterogeneities in Federated Learning with Unlimited Staleness
Haoming Wang, Wei Gao
Reinforcement Active Client Selection for Federated Heterogeneous Graph Learning
Jia Wang, Yawen Li, Yingxia Shao et al.
Handling Spatial-Temporal Data Heterogeneity for Federated Continual Learning via Tail Anchor
Hao Yu, Xin Yang, Le Zhang et al.
FedVAD: Enhancing Federated Video Anomaly Detection with GPT-Driven Semantic Distillation
Fan Qi, Ruijie Pan, Huaiwen Zhang et al.
Efficient Adaptive Federated Optimization
Su Hyeong Lee, Sidharth Sharma, Manzil Zaheer et al.
FedSVD: Adaptive Orthogonalization for Private Federated Learning with LoRA
Seanie Lee, Sangwoo Park, Dong Bok Lee et al.
Exact and Linear Convergence for Federated Learning under Arbitrary Client Participation is Attainable
Bicheng Ying, Zhe Li, Haibo Yang
Generalization in Federated Learning: A Conditional Mutual Information Framework
Ziqiao Wang, Cheng Long, Yongyi Mao
Federated In-Context Learning: Iterative Refinement for Improved Answer Quality
Ruhan Wang, Zhiyong Wang, Chengkai Huang et al.
Does One-shot Give the Best Shot? Mitigating Model Inconsistency in One-shot Federated Learning
Hui Zeng, Wenke Huang, Tongqing Zhou et al.
Splitting with Importance-aware Updating for Heterogeneous Federated Learning with Large Language Models
Yangxu Liao, Wenke Huang, Guancheng Wan et al.
Resource-Constrained Federated Continual Learning: What Does Matter?
Yichen Li, Yuying Wang, Jiahua Dong et al.
Ferret: An Efficient Online Continual Learning Framework under Varying Memory Constraints
Yuhao Zhou, Yuxin Tian, Jindi Lv et al.
FCOM: A Federated Collaborative Online Monitoring Framework via Representation Learning
Tanapol Kosolwattana, Huazheng Wang, Raed Al Kontar et al.
Learn How to Query from Unlabeled Data Streams in Federated Learning
Yuchang Sun, Xinran Li, Tao Lin et al.
Mitigating the Privacy–Utility Trade-off in Decentralized Federated Learning via f-Differential Privacy
Xiang Li, Chendi Wang, Buxin Su et al.