Understanding Server-Assisted Federated Learning in the Presence of
Incomplete Client Participation

Understanding Server-Assisted Federated Learning in the Presence of Incomplete Client Participation

4 May 2024

Haibo Yang

Prashant Khanduri

Papers citing "Understanding Server-Assisted Federated Learning in the Presence of Incomplete Client Participation"

13 / 13 papers shown

Title
A Unified Analysis of Federated Learning with Arbitrary Client Participation Shiqiang Wang Mingyue Ji FedML 76 56 0 31 Dec 2024
LoCoDL: Communication-Efficient Distributed Learning with Local Training and Compression Laurent Condat Artavazd Maranjyan Peter Richtárik 92 5 0 07 Mar 2024
On the Convergence of Federated Averaging with Cyclic Client Participation Yae Jee Cho Pranay Sharma Gauri Joshi Zheng Xu Satyen Kale Tong Zhang FedML 71 29 0 06 Feb 2023
Can 5th Generation Local Training Methods Support Client Sampling? Yes! Michal Grudzieñ Grigory Malinovsky Peter Richtárik 63 29 0 29 Dec 2022
Anarchic Federated Learning Haibo Yang Xin Zhang Prashant Khanduri Jia Liu FedML 31 58 0 23 Aug 2021
A Field Guide to Federated Optimization Jianyu Wang Zachary B. Charles Zheng Xu Gauri Joshi H. B. McMahan ... Mi Zhang Tong Zhang Chunxiang Zheng Chen Zhu Wennan Zhu FedML 252 415 0 14 Jul 2021
No Fear of Heterogeneity: Classifier Calibration for Federated Learning with Non-IID Data Mi Luo Fei Chen Dapeng Hu Yifan Zhang Jian Liang Jiashi Feng FedML 66 336 0 09 Jun 2021
Linear Convergence in Federated Learning: Tackling Client Heterogeneity and Sparse Gradients A. Mitra Rayana H. Jaafar George J. Pappas Hamed Hassani FedML 72 158 0 14 Feb 2021
Optimal Client Sampling for Federated Learning Jiajun He Samuel Horváth Peter Richtárik FedML 65 195 0 26 Oct 2020
Tackling the Objective Inconsistency Problem in Heterogeneous Federated Optimization Jianyu Wang Qinghua Liu Hao Liang Gauri Joshi H. Vincent Poor MoMe FedML 45 1,321 0 15 Jul 2020
Towards Federated Learning at Scale: System Design Keith Bonawitz Hubert Eichner W. Grieskamp Dzmitry Huba A. Ingerman ... H. B. McMahan Timon Van Overveldt David Petrou Daniel Ramage Jason Roselander FedML 93 2,652 0 04 Feb 2019
Communication-Efficient Learning of Deep Networks from Decentralized Data H. B. McMahan Eider Moore Daniel Ramage S. Hampson Blaise Agüera y Arcas FedML 239 17,328 0 17 Feb 2016
Refined Error Bounds for Several Learning Algorithms Steve Hanneke 95 38 0 22 Dec 2015