On the Unreasonable Effectiveness of Federated Averaging with
Heterogeneous Data

On the Unreasonable Effectiveness of Federated Averaging with Heterogeneous Data

9 June 2022

Tong Zhang

Papers citing "On the Unreasonable Effectiveness of Federated Averaging with Heterogeneous Data"

7 / 7 papers shown

Title
Understanding Generalization of Federated Learning: the Trade-off between Model Stability and Optimization Dun Zeng Zheshun Wu Shiyu Liu Yu Pan Xiaoying Tang Zenglin Xu MLT FedML 87 1 0 25 Nov 2024
A New Theoretical Perspective on Data Heterogeneity in Federated Optimization Jiayi Wang Shiqiang Wang Rong-Rong Chen Mingyue Ji FedML 28 1 0 22 Jul 2024
The Limits and Potentials of Local SGD for Distributed Heterogeneous Learning with Intermittent Communication Kumar Kshitij Patel Margalit Glasgow Ali Zindari Lingxiao Wang Sebastian U. Stich Ziheng Cheng Nirmit Joshi Nathan Srebro 44 6 0 19 May 2024
Distributed Personalized Empirical Risk Minimization Yuyang Deng Mohammad Mahdi Kamani Pouria Mahdavinia M. Mahdavi 21 4 0 26 Oct 2023
Distributed Stochastic Optimization under a General Variance Condition Kun-Yen Huang Xiao Li Shin-Yi Pu FedML 37 5 0 30 Jan 2023
Learning to Generate Image Embeddings with User-level Differential Privacy Zheng Xu Maxwell D. Collins Yuxiao Wang Liviu Panait Sewoong Oh S. Augenstein Ting Liu Florian Schroff H. B. McMahan FedML 30 29 0 20 Nov 2022
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 175 411 0 14 Jul 2021