Anchor Sampling for Federated Learning with Partial Client Participation

Anchor Sampling for Federated Learning with Partial Client Participation

13 June 2022

Jing Gao

Papers citing "Anchor Sampling for Federated Learning with Partial Client Participation"

11 / 11 papers shown

Title
FedFetch: Faster Federated Learning with Adaptive Downstream Prefetching Qifan Yan Andrew Liu Shiqi He Mathias Lécuyer Ivan Beschastnikh FedML 36 0 0 21 Apr 2025
Scalable Decentralized Learning with Teleportation Yuki Takezawa Sebastian U. Stich 54 1 0 25 Jan 2025
Hierarchical Federated Learning with Multi-Timescale Gradient Correction Wenzhi Fang Dong-Jun Han Evan Chen Shiqiang Wang Christopher G. Brinton 24 4 0 27 Sep 2024
Byzantine-resilient Federated Learning Employing Normalized Gradients on Non-IID Datasets Shiyuan Zuo Xingrun Yan Rongfei Fan Li Shen Puning Zhao Jie Xu Han Hu FedML 36 1 0 18 Aug 2024
FIARSE: Model-Heterogeneous Federated Learning via Importance-Aware Submodel Extraction Feijie Wu Xingchen Wang Yaqing Wang Tianci Liu Lu Su Jing Gao FedML 43 3 0 28 Jul 2024
FedBiOT: LLM Local Fine-tuning in Federated Learning without Full Model Feijie Wu Zitao Li Yaliang Li Bolin Ding Jing Gao 29 41 0 25 Jun 2024
DASHA: Distributed Nonconvex Optimization with Communication Compression, Optimal Oracle Complexity, and No Client Synchronization A. Tyurin Peter Richtárik 37 17 0 02 Feb 2022
Linear Convergence in Federated Learning: Tackling Client Heterogeneity and Sparse Gradients A. Mitra Rayana H. Jaafar George J. Pappas Hamed Hassani FedML 55 157 0 14 Feb 2021
Adaptivity of Stochastic Gradient Methods for Nonconvex Optimization Samuel Horváth Lihua Lei Peter Richtárik Michael I. Jordan 55 30 0 13 Feb 2020
Stochastic Nonconvex Optimization with Large Minibatches Weiran Wang Nathan Srebro 34 26 0 25 Sep 2017
Linear Convergence of Gradient and Proximal-Gradient Methods Under the Polyak-Łojasiewicz Condition Hamed Karimi J. Nutini Mark W. Schmidt 119 1,198 0 16 Aug 2016