Gradient Scheduling with Global Momentum for Non-IID Data Distributed Asynchronous Training

21 February 2019

Papers citing "Gradient Scheduling with Global Momentum for Non-IID Data Distributed Asynchronous Training"

5 / 5 papers shown

Title
Improving Federated Learning Communication Efficiency with Global Momentum Fusion for Gradient Compression Schemes Chun-Chih Kuo Ted T. Kuo Chia-Yu Lin FedML 13 1 0 17 Nov 2022
AsyncFedED: Asynchronous Federated Learning with Euclidean Distance based Adaptive Weight Aggregation Qiyuan Wang Qianqian Yang Shibo He Zhiguo Shi Jiming Chen FedML 37 25 0 27 May 2022
Towards Efficient and Stable K-Asynchronous Federated Learning with Unbounded Stale Gradients on Non-IID Data Zihao Zhou Yanan Li Xuebin Ren Shusen Yang 22 29 0 02 Mar 2022
Aggregation Delayed Federated Learning Ye Xue Diego Klabjan Yuan Luo FedML OOD 23 5 0 17 Aug 2021
Cross-Gradient Aggregation for Decentralized Learning from Non-IID data Yasaman Esfandiari Sin Yong Tan Zhanhong Jiang Aditya Balu Ethan Herron C. Hegde S. Sarkar OOD 17 50 0 02 Mar 2021