Walk for Learning: A Random Walk Approach for Federated Learning from
Heterogeneous Data

Walk for Learning: A Random Walk Approach for Federated Learning from Heterogeneous Data

1 June 2022

Papers citing "Walk for Learning: A Random Walk Approach for Federated Learning from Heterogeneous Data"

11 / 11 papers shown

Title
Private Weighted Random Walk Stochastic Gradient Descent Ghadir Ayache S. E. Rouayheb FedML 34 19 0 03 Sep 2020
Tackling the Objective Inconsistency Problem in Heterogeneous Federated Optimization Jianyu Wang Qinghua Liu Hao Liang Gauri Joshi H. Vincent Poor MoMe FedML 55 1,332 0 15 Jul 2020
Advances and Open Problems in Federated Learning Peter Kairouz H. B. McMahan Brendan Avent A. Bellet M. Bennis ... Zheng Xu Qiang Yang Felix X. Yu Han Yu Sen Zhao FedML AI4CE 226 6,247 0 10 Dec 2019
On the Convergence of Local Descent Methods in Federated Learning Farzin Haddadpour M. Mahdavi FedML 74 271 0 31 Oct 2019
Tighter Theory for Local SGD on Identical and Heterogeneous Data Ahmed Khaled Konstantin Mishchenko Peter Richtárik 71 433 0 10 Sep 2019
Adaptive Online Learning in Dynamic Environments Lijun Zhang Shiyin Lu Zhi Zhou 57 185 0 25 Oct 2018
On Markov Chain Gradient Descent Tao Sun Yuejiao Sun W. Yin BDL 41 102 0 12 Sep 2018
Adaptive Federated Learning in Resource Constrained Edge Computing Systems Shiqiang Wang Tiffany Tuor Theodoros Salonidis K. Leung C. Makaya T. He Kevin S. Chan 242 1,706 0 14 Apr 2018
SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives Aaron Defazio Francis R. Bach Simon Lacoste-Julien ODL 131 1,823 0 01 Jul 2014
A Proximal Stochastic Gradient Method with Progressive Variance Reduction Lin Xiao Tong Zhang ODL 150 738 0 19 Mar 2014
Ergodic Mirror Descent John C. Duchi Alekh Agarwal M. Johansson Michael I. Jordan 179 125 0 24 May 2011