Slashing Communication Traffic in Federated Learning by Transmitting Clustered Model Updates

10 May 2021

Papers citing "Slashing Communication Traffic in Federated Learning by Transmitting Clustered Model Updates"

7 / 7 papers shown

Title
Communication-Efficient Federated Learning through Adaptive Weight Clustering and Server-Side Distillation Vasileios Tsouvalas Aaqib Saeed T. Ozcelebi N. Meratnia FedML 34 6 0 25 Jan 2024
Joint Optimization of Energy Consumption and Completion Time in Federated Learning Xinyu Zhou Jun Zhao Huimei Han C. Guet FedML 43 27 0 29 Sep 2022
A Fast Blockchain-based Federated Learning Framework with Compressed Communications Laizhong Cui Xiaoxin Su Yipeng Zhou FedML 8 23 0 12 Aug 2022
Towards Efficient Communications in Federated Learning: A Contemporary Survey Zihao Zhao Yuzhu Mao Yang Liu Linqi Song Ouyang Ye Xinlei Chen Wenbo Ding FedML 51 59 0 02 Aug 2022
Towards Effective Clustered Federated Learning: A Peer-to-peer Framework with Adaptive Neighbor Matching Zexi Li Jiaxun Lu Shuang Luo Didi Zhu Yunfeng Shao Yinchuan Li Zhimeng Zhang Yongheng Wang Chao-Xiang Wu FedML 30 36 0 23 Mar 2022
Optimal Rate Adaption in Federated Learning with Compressed Communications Laizhong Cui Xiaoxin Su Yipeng Zhou Jiangchuan Liu FedML 33 38 0 13 Dec 2021
Adaptive Federated Learning in Resource Constrained Edge Computing Systems Shiqiang Wang Tiffany Tuor Theodoros Salonidis K. Leung C. Makaya T. He Kevin S. Chan 144 1,685 0 14 Apr 2018