Adaptive Self-Distillation for Minimizing Client Drift in Heterogeneous Federated Learning

31 May 2023

Papers citing "Adaptive Self-Distillation for Minimizing Client Drift in Heterogeneous Federated Learning"

4 / 4 papers shown

Title
FedSpeed: Larger Local Interval, Less Communication Round, and Higher Generalization Accuracy Yan Sun Li Shen Tiansheng Huang Liang Ding Dacheng Tao FedML 29 50 0 21 Feb 2023
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 167 410 0 14 Jul 2021
The Future of Digital Health with Federated Learning Nicola Rieke Jonny Hancox Wenqi Li Fausto Milletari H. Roth ... Ronald M. Summers Andrew Trask Daguang Xu Maximilian Baust M. Jorge Cardoso OOD 174 1,690 0 18 Mar 2020
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima N. Keskar Dheevatsa Mudigere J. Nocedal M. Smelyanskiy P. T. P. Tang ODL 273 2,878 0 15 Sep 2016