FedADMM-InSa: An Inexact and Self-Adaptive ADMM for Federated Learning

21 February 2024

Papers citing "FedADMM-InSa: An Inexact and Self-Adaptive ADMM for Federated Learning"

8 / 8 papers shown

Title
Distributed Event-Based Learning via ADMM Güner Dilsad Er Sebastian Trimpe Michael Muehlebach FedML 64 2 0 17 May 2024
Approximate and Weighted Data Reconstruction Attack in Federated Learning Yongcun Song Ziqi Wang Enrique Zuazua AAML FedML 62 4 0 13 Aug 2023
FedADMM: A Federated Primal-Dual Algorithm Allowing Partial Participation Han Wang Siddartha Marella James Anderson FedML 32 39 0 28 Mar 2022
Towards Personalized Federated Learning A. Tan Han Yu Li-zhen Cui Qiang Yang FedML AI4CE 289 855 0 01 Mar 2021
Tackling the Objective Inconsistency Problem in Heterogeneous Federated Optimization Jianyu Wang Qinghua Liu Hao Liang Gauri Joshi H. Vincent Poor MoMe FedML 43 1,321 0 15 Jul 2020
A Survey on Federated Learning Systems: Vision, Hype and Reality for Data Privacy and Protection Yue Liu Zeyi Wen Zhaomin Wu Sixu Hu Naibo Wang Yuan N. Li Xu Liu Bingsheng He FedML 74 990 0 23 Jul 2019
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 88 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 234 17,328 0 17 Feb 2016