"federated learning" Papers
178 papers found • Page 1 of 4
Conference
A Fair Federated Learning Method for Handling Client Participation Probability Inconsistencies in Heterogeneous Environments
Siyuan Wu, Yongzhe Jia, Haolong Xiang et al.
A New Federated Learning Framework Against Gradient Inversion Attacks
Pengxin Guo, Shuang Zeng, Wenhao Chen et al.
Bi-Directional Communication-Efficient Stochastic FL via Remote Source Generation
Maximilian Egger, Rawad Bitar, Antonia Wachter-Zeh et al.
BSemiFL: Semi-supervised Federated Learning via a Bayesian Approach
Haozhao Wang, Shengyu Wang, Jiaming Li et al.
Can Textual Gradient Work in Federated Learning?
Minghui Chen, Ruinan Jin, Wenlong Deng et al.
Class-wise Balancing Data Replay for Federated Class-Incremental Learning
Zhuang Qi, Ying-Peng Tang, Lei Meng et al.
Connecting Federated ADMM to Bayes
Siddharth Swaroop, Mohammad Emtiyaz Khan, Finale Doshi-Velez
Covariances for Free: Exploiting Mean Distributions for Training-free Federated Learning
Dipam Goswami, Simone Magistri, Kai Wang et al.
Data-Free Black-Box Federated Learning via Zeroth-Order Gradient Estimation
Xinge Ma, Jin Wang, Xuejie Zhang
Debiasing Federated Learning with Correlated Client Participation
Zhenyu Sun, Ziyang Zhang, Zheng Xu et al.
Defending Against Sophisticated Poisoning Attacks with RL-based Aggregation in Federated Learning
Yujing Wang, Hainan Zhang, Sijia Wen et al.
Detecting Backdoor Attacks in Federated Learning via Direction Alignment Inspection
Jiahao Xu, Zikai Zhang, Rui Hu
Differentially Private Federated Low Rank Adaptation Beyond Fixed-Matrix
Ming Wen, Jiaqi Zhu, Yuedong Xu et al.
Diffusion Federated Dataset
SEOKJU HAHN, Junghye Lee
DKDR: Dynamic Knowledge Distillation for Reliability in Federated Learning
Yueyang Yuan, Wenke Huang, Guancheng Wan et al.
DualGFL: Federated Learning with a Dual-Level Coalition-Auction Game
Xiaobing Chen, Xiangwei Zhou, Songyang Zhang et al.
EBS-CFL: Efficient and Byzantine-robust Secure Clustered Federated Learning
Zhiqiang Li, Haiyong Bao, Menghong Guan et al.
Efficient Adaptive Federated Optimization
Su Hyeong Lee, Sidharth Sharma, Manzil Zaheer et al.
Efficient Federated Learning against Byzantine Attacks and Data Heterogeneity via Aggregating Normalized Gradients
Shiyuan Zuo, Xingrun Yan, Rongfei Fan et al.
Emerging Safety Attack and Defense in Federated Instruction Tuning of Large Language Models
Rui Ye, Jingyi Chai, Xiangrui Liu et al.
Exact and Linear Convergence for Federated Learning under Arbitrary Client Participation is Attainable
Bicheng Ying, Zhe Li, Haibo Yang
Exploit Gradient Skewness to Circumvent Byzantine Defenses for Federated Learning
Yuchen Liu, Chen Chen, Lingjuan Lyu et al.
Exploring Vacant Classes in Label-Skewed Federated Learning
Kuangpu Guo, Yuhe Ding, Jian Liang et al.
FCOM: A Federated Collaborative Online Monitoring Framework via Representation Learning
Tanapol Kosolwattana, Huazheng Wang, Raed Al Kontar et al.
FedAWA: Adaptive Optimization of Aggregation Weights in Federated Learning Using Client Vectors
Changlong Shi, He Zhao, Bingjie Zhang et al.
FedBiP: Heterogeneous One-Shot Federated Learning with Personalized Latent Diffusion Models
Haokun Chen, Hang Li, Yao Zhang et al.
FedCross: Intertemporal Federated Learning Under Evolutionary Games
Jianfeng Lu, Ying Zhang, Riheng Jia et al.
FedEL: Federated Elastic Learning for Heterogeneous Devices
Letian Zhang, Bo Chen, Jieming Bian et al.
Federated Binary Matrix Factorization Using Proximal Optimization
Sebastian Dalleiger, Jilles Vreeken, Michael Kamp
Federated Continual Instruction Tuning
Haiyang Guo, Fanhu Zeng, Fei Zhu et al.
Federated Domain Generalization with Data-free On-server Matching Gradient
Binh Nguyen, Minh-Duong Nguyen, Jinsun Park et al.
Federated Few-Shot Class-Incremental Learning
Muhammad Anwar Masum, Mahardhika Pratama, Lin Liu et al.
Federated In-Context Learning: Iterative Refinement for Improved Answer Quality
Ruhan Wang, Zhiyong Wang, Chengkai Huang et al.
Federated Learning with Domain Shift Eraser
Zheng Wang, Zihui Wang, Zheng Wang et al.
Federated Residual Low-Rank Adaption of Large Language Models
Yunlu Yan, Chun-Mei Feng, Wangmeng Zuo et al.
Federated t-SNE and UMAP for Distributed Data Visualization
Dong Qiao, Xinxian Ma, Jicong Fan
Federated Unlearning with Gradient Descent and Conflict Mitigation
Zibin Pan, Zhichao Wang, Chi Li et al.
Federated Unsupervised Domain Generalization Using Global and Local Alignment of Gradients
Farhad Pourpanah, Mahdiyar Molahasani, Milad Soltany et al.
FedFACT: A Provable Framework for Controllable Group-Fairness Calibration in Federated Learning
Li Zhang, Zhongxuan Han, XiaoHua Feng et al.
FedGPS: Statistical Rectification Against Data Heterogeneity in Federated Learning
Zhiqin Yang, Yonggang Zhang, Chenxin Li et al.
FedLPA: Local Prior Alignment for Heterogeneous Federated Generalized Category Discovery
Geeho Kim, Jinu Lee, Bohyung Han
FedLWS: Federated Learning with Adaptive Layer-wise Weight Shrinking
Changlong Shi, Jinmeng Li, He Zhao et al.
FedMVP: Federated Multimodal Visual Prompt Tuning for Vision-Language Models
Mainak Singha, Subhankar Roy, Sarthak Mehrotra et al.
FedQS: Optimizing Gradient and Model Aggregation for Semi-Asynchronous Federated Learning
Yunbo Li, Jiaping Gui, Zhihang Deng et al.
FedRACE: A Hierarchical and Statistical Framework for Robust Federated Learning
Gang Yan, Sikai Yang, Wan Du
FedRAM: Federated Reweighting and Aggregation for Multi-Task Learning
Fan Wu, Xinyu Yan, Jiabei Liu et al.
FedRTS: Federated Robust Pruning via Combinatorial Thompson Sampling
Hong Huang, Jinhai Yang, Yuan Chen et al.
FedRW: Efficient Privacy-Preserving Data Reweighting for Enhancing Federated Learning of Language Models
Pukang Ye, Luo Junwei, Jiachen Shen et al.
FedVLA: Federated Vision-Language-Action Learning with Dual Gating Mixture-of-Experts for Robotic Manipulation
Cui Miao, Tao Chang, meihan wu et al.
FedWMSAM: Fast and Flat Federated Learning via Weighted Momentum and Sharpness-Aware Minimization
Tianle Li, Yongzhi Huang, Linshan Jiang et al.