Convergence of Distributed Stochastic Variance Reduced Methods without Sampling Extra Data

29 May 2019

Papers citing "Convergence of Distributed Stochastic Variance Reduced Methods without Sampling Extra Data"

5 / 5 papers shown

Title
Asynchronous Training Schemes in Distributed Learning with Time Delay Haoxiang Wang Zhanhong Jiang Chao Liu Soumik Sarkar D. Jiang Young M. Lee 42 2 0 28 Aug 2022
Communication-efficient Distributed Newton-like Optimization with Gradients and M-estimators Ziyan Yin 37 0 0 13 Jul 2022
Distributed Newton-Type Methods with Communication Compression and Bernoulli Aggregation Rustem Islamov Xun Qian Slavomír Hanzely M. Safaryan Peter Richtárik 42 16 0 07 Jun 2022
FedPD: A Federated Learning Framework with Optimal Rates and Adaptivity to Non-IID Data Xinwei Zhang Mingyi Hong S. Dhople W. Yin Yang Liu FedML 23 228 0 22 May 2020
A Proximal Stochastic Gradient Method with Progressive Variance Reduction Lin Xiao Tong Zhang ODL 93 737 0 19 Mar 2014