First Order Methods with Markovian Noise: from Acceleration to
Variational Inequalities

First Order Methods with Markovian Noise: from Acceleration to Variational Inequalities

25 May 2023

Aleksandr Beznosikov

Marina Sheshukova

Alexander Gasnikov

Papers citing "First Order Methods with Markovian Noise: from Acceleration to Variational Inequalities"

10 / 10 papers shown

Title
Achieving Tighter Finite-Time Rates for Heterogeneous Federated Stochastic Approximation under Markovian Sampling Feng Zhu Aritra Mitra Robert W. Heath FedML 31 0 0 15 Apr 2025
Debiasing Federated Learning with Correlated Client Participation Zhenyu Sun Ziyang Zhang Zheng Xu Gauri Joshi Pranay Sharma Ermin Wei FedML 17 0 0 02 Oct 2024
Queuing dynamics of asynchronous Federated Learning Louis Leconte Matthieu Jonckheere S. Samsonov Eric Moulines FedML 19 3 0 12 Feb 2024
Dynamic Byzantine-Robust Learning: Adapting to Switching Byzantine Workers Ron Dorfman Naseem Yehya Kfir Y. Levy 17 1 0 05 Feb 2024
Non-asymptotic Analysis of Biased Adaptive Stochastic Approximation Sobihan Surendran Antoine Godichon-Baggioni Adeline Fermanian Sylvain Le Corff 19 1 0 05 Feb 2024
Stochastic optimization with arbitrary recurrent data sampling William G. Powell Hanbaek Lyu 8 0 0 15 Jan 2024
Markov Chain Mirror Descent On Data Federation Yawei Zhao FedML 9 1 0 26 Sep 2023
Adapting to Mixing Time in Stochastic Optimization with Markovian Data Ron Dorfman Kfir Y. Levy 22 28 0 09 Feb 2022
Stochastic Variance Reduction for Variational Inequality Methods Ahmet Alacaoglu Yura Malitsky 51 61 0 16 Feb 2021
Convex Sparse Matrix Factorizations Francis R. Bach Julien Mairal Jean Ponce 121 143 0 10 Dec 2008