EF-BV: A Unified Theory of Error Feedback and Variance Reduction Mechanisms for Biased and Unbiased Compression in Distributed Optimization

9 May 2022

Papers citing "EF-BV: A Unified Theory of Error Feedback and Variance Reduction Mechanisms for Biased and Unbiased Compression in Distributed Optimization"

6 / 6 papers shown

Title
LoCoDL: Communication-Efficient Distributed Learning with Local Training and Compression Laurent Condat A. Maranjyan Peter Richtárik 39 3 0 07 Mar 2024
GradSkip: Communication-Accelerated Local Gradient Methods with Better Computational Complexity A. Maranjyan M. Safaryan Peter Richtárik 34 13 0 28 Oct 2022
Permutation Compressors for Provably Faster Distributed Nonconvex Optimization Rafal Szlendak A. Tyurin Peter Richtárik 122 35 0 07 Oct 2021
EF21 with Bells & Whistles: Practical Algorithmic Extensions of Modern Error Feedback Ilyas Fatkhullin Igor Sokolov Eduard A. Gorbunov Zhize Li Peter Richtárik 46 44 0 07 Oct 2021
Linearly Converging Error Compensated SGD Eduard A. Gorbunov D. Kovalev Dmitry Makarenko Peter Richtárik 163 77 0 23 Oct 2020
Linear Convergence of Gradient and Proximal-Gradient Methods Under the Polyak-Łojasiewicz Condition Hamed Karimi J. Nutini Mark W. Schmidt 139 1,198 0 16 Aug 2016