Communication Compression for Byzantine Robust Learning: New Efficient Algorithms and Improved Rates

15 October 2023

Papers citing "Communication Compression for Byzantine Robust Learning: New Efficient Algorithms and Improved Rates"

9 / 9 papers shown

Title
Byzantine-Robust and Communication-Efficient Distributed Learning via Compressed Momentum Filtering Changxin Liu Yanghao Li Yuhao Yi Karl H. Johansson FedML 16 0 0 13 Sep 2024
A survey on secure decentralized optimization and learning Changxin Liu Nicola Bastianello Wei Huo Yang Shi Karl H. Johansson 18 1 0 16 Aug 2024
Streamlining in the Riemannian Realm: Efficient Riemannian Optimization with Loopless Variance Reduction Yury Demidovich Grigory Malinovsky Peter Richtárik 42 2 0 11 Mar 2024
EF21-P and Friends: Improved Theoretical Communication Complexity for Distributed Optimization with Bidirectional Compression Kaja Gruntkowska A. Tyurin Peter Richtárik 36 18 0 30 Sep 2022
DASHA: Distributed Nonconvex Optimization with Communication Compression, Optimal Oracle Complexity, and No Client Synchronization A. Tyurin Peter Richtárik 26 17 0 02 Feb 2022
Permutation Compressors for Provably Faster Distributed Nonconvex Optimization Rafal Szlendak A. Tyurin Peter Richtárik 113 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 36 44 0 07 Oct 2021
Privacy and Robustness in Federated Learning: Attacks and Defenses Lingjuan Lyu Han Yu Xingjun Ma Chen Chen Lichao Sun Jun Zhao Qiang Yang Philip S. Yu FedML 169 244 0 07 Dec 2020
Linearly Converging Error Compensated SGD Eduard A. Gorbunov D. Kovalev Dmitry Makarenko Peter Richtárik 149 77 0 23 Oct 2020