On the Performance of Gradient Tracking with Local Updates

On the Performance of Gradient Tracking with Local Updates

10 October 2022

Edward Duc Hien Nguyen

Sulaiman A. Alghunaim

César A. Uribe

Papers citing "On the Performance of Gradient Tracking with Local Updates"

12 / 12 papers shown

Title
Decentralized Nonconvex Composite Federated Learning with Gradient Tracking and Momentum Yuan Zhou Xinli Shi Xuelong Li Jiachen Zhong G. Wen Jinde Cao FedML 39 0 0 17 Apr 2025
Fast Decentralized Gradient Tracking for Federated Minimax Optimization with Local Updates Chris Junchi Li 22 0 0 07 May 2024
Robust Decentralized Learning with Local Updates and Gradient Tracking Sajjad Ghiasvand Amirhossein Reisizadeh Mahnoosh Alizadeh Ramtin Pedarsani 28 3 0 02 May 2024
The Effectiveness of Local Updates for Decentralized Learning under Data Heterogeneity Tongle Wu Ying Sun 28 0 0 23 Mar 2024
Communication-Efficient Federated Optimization over Semi-Decentralized Networks He Wang Yuejie Chi FedML 18 2 0 30 Nov 2023
Revisiting Decentralized ProxSkip: Achieving Linear Speedup Luyao Guo Sulaiman A. Alghunaim Kun Yuan Laurent Condat Jinde Cao FedML 19 1 0 12 Oct 2023
Momentum Benefits Non-IID Federated Learning Simply and Provably Ziheng Cheng Xinmeng Huang Pengfei Wu Kun Yuan FedML 18 16 0 28 Jun 2023
On the Computation-Communication Trade-Off with A Flexible Gradient Tracking Approach Yan Huang Jinming Xu 12 2 0 12 Jun 2023
Decentralized Gradient Tracking with Local Steps Yue Liu Tao R. Lin Anastasia Koloskova Sebastian U. Stich 9 36 0 03 Jan 2023
BlueFog: Make Decentralized Algorithms Practical for Optimization and Deep Learning Bicheng Ying Kun Yuan Hanbin Hu Yiming Chen W. Yin FedML 29 27 0 08 Nov 2021
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
Distributed Pareto Optimization via Diffusion Strategies Jianshu Chen A. H. Sayed 55 174 0 13 Aug 2012