Stochastic Gradient Descent-Ascent: Unified Theory and New Efficient Methods

15 February 2022

Papers citing "Stochastic Gradient Descent-Ascent: Unified Theory and New Efficient Methods"

31 / 31 papers shown

Title
Properties of Fixed Points of Generalised Extra Gradient Methods Applied to Min-Max Problems Amir Ali Farzin Yuen-Man Pun Philipp Braun Iman Shames 23 0 0 03 Apr 2025
Sharpness-Aware Minimization: General Analysis and Improved Rates Dimitris Oikonomou Nicolas Loizou 60 0 0 04 Mar 2025
Shuffling Gradient-Based Methods for Nonconvex-Concave Minimax Optimization Quoc Tran-Dinh Trang H. Tran Lam M. Nguyen 27 0 0 29 Oct 2024
Gradient-based Learning in State-based Potential Games for Self-Learning Production Systems Steve Yuwono Marlon Löppenberg Dorothea Schwung Andreas Schwung 20 2 0 14 Jun 2024
Dissipative Gradient Descent Ascent Method: A Control Theory Inspired Algorithm for Min-max Optimization Tianqi Zheng Nicolas Loizou Pengcheng You Enrique Mallada 23 1 0 14 Mar 2024
Stochastic Extragradient with Random Reshuffling: Improved Convergence for Variational Inequalities Konstantinos Emmanouilidis René Vidal Nicolas Loizou 21 2 0 11 Mar 2024
Balancing Act: Constraining Disparate Impact in Sparse Models Meraj Hashemizadeh Juan Ramirez Rohan Sukumaran G. Farnadi Simon Lacoste-Julien Jose Gallego-Posada 30 4 0 31 Oct 2023
DePAint: A Decentralized Safe Multi-Agent Reinforcement Learning Algorithm considering Peak and Average Constraints Raheeb Hassan K. M. S. Wadith Md. Mamun-or Rashid Md. Mosaddek Khan 17 2 0 22 Oct 2023
Communication Compression for Byzantine Robust Learning: New Efficient Algorithms and Improved Rates Ahmad Rammal Kaja Gruntkowska Nikita Fedin Eduard A. Gorbunov Peter Richtárik 29 5 0 15 Oct 2023
Variance Reduced Halpern Iteration for Finite-Sum Monotone Inclusions Xu Cai Ahmet Alacaoglu Jelena Diakonikolas 30 7 0 04 Oct 2023
Distributed Extra-gradient with Optimal Complexity and Communication Guarantees Ali Ramezani-Kebrya Kimon Antonakopoulos Igor Krawczuk Justin Deschenaux V. Cevher 24 2 0 17 Aug 2023
Stochastic Methods in Variational Inequalities: Ergodicity, Bias and Refinements Emmanouil-Vasileios Vlatakis-Gkaragkounis Angeliki Giannou Yudong Chen Qiaomin Xie 11 4 0 28 Jun 2023
Omega: Optimistic EMA Gradients Juan Ramirez Rohan Sukumaran Quentin Bertrand Gauthier Gidel 16 0 0 13 Jun 2023
A Central Limit Theorem for Algorithmic Estimator of Saddle Point Abhishek Roy Yian Ma 14 1 0 09 Jun 2023
Communication-Efficient Gradient Descent-Accent Methods for Distributed Variational Inequalities: Unified Analysis and Local Updates Siqi Zhang S. Choudhury Sebastian U. Stich Nicolas Loizou FedML 11 3 0 08 Jun 2023
First Order Methods with Markovian Noise: from Acceleration to Variational Inequalities Aleksandr Beznosikov S. Samsonov Marina Sheshukova Alexander Gasnikov A. Naumov Eric Moulines 29 14 0 25 May 2023
Unified analysis of SGD-type methods Eduard A. Gorbunov 19 2 0 29 Mar 2023
A Finite-Sample Analysis of Payoff-Based Independent Learning in Zero-Sum Stochastic Games Zaiwei Chen K. Zhang Eric Mazumdar Asuman Ozdaglar Adam Wierman 41 6 0 03 Mar 2023
Single-Call Stochastic Extragradient Methods for Structured Non-monotone Variational Inequalities: Improved Analysis under Weaker Conditions S. Choudhury Eduard A. Gorbunov Nicolas Loizou 22 13 0 27 Feb 2023
Solving stochastic weak Minty variational inequalities without increasing batch size Thomas Pethick Olivier Fercoq P. Latafat Panagiotis Patrinos V. Cevher 8 23 0 17 Feb 2023
SGDA with shuffling: faster convergence for nonconvex-PŁ minimax optimization Hanseul Cho Chulhee Yun 8 9 0 12 Oct 2022
SARAH-based Variance-reduced Algorithm for Stochastic Finite-sum Cocoercive Variational Inequalities Aleksandr Beznosikov Alexander Gasnikov 14 1 0 12 Oct 2022
Smooth Monotone Stochastic Variational Inequalities and Saddle Point Problems: A Survey Aleksandr Beznosikov Boris Polyak Eduard A. Gorbunov D. Kovalev Alexander Gasnikov 32 31 0 29 Aug 2022
Clipped Stochastic Methods for Variational Inequalities with Heavy-Tailed Noise Eduard A. Gorbunov Marina Danilova David Dobre Pavel Dvurechensky Alexander Gasnikov Gauthier Gidel 11 24 0 02 Jun 2022
Variance Reduction is an Antidote to Byzantines: Better Rates, Weaker Assumptions and Communication Compression as a Cherry on the Top Eduard A. Gorbunov Samuel Horváth Peter Richtárik Gauthier Gidel AAML 11 0 0 01 Jun 2022
Distributed Methods with Absolute Compression and Error Compensation Marina Danilova Eduard A. Gorbunov 11 4 0 04 Mar 2022
ProxSkip: Yes! Local Gradient Steps Provably Lead to Communication Acceleration! Finally! Konstantin Mishchenko Grigory Malinovsky Sebastian U. Stich Peter Richtárik 11 148 0 18 Feb 2022
Optimal Algorithms for Decentralized Stochastic Variational Inequalities D. Kovalev Aleksandr Beznosikov Abdurakhmon Sadiev Michael Persiianov Peter Richtárik Alexander Gasnikov 30 34 0 06 Feb 2022
Decentralized Local Stochastic Extra-Gradient for Variational Inequalities Aleksandr Beznosikov Pavel Dvurechensky Anastasia Koloskova V. Samokhin Sebastian U. Stich Alexander Gasnikov 13 43 0 15 Jun 2021
Stochastic Variance Reduction for Variational Inequality Methods Ahmet Alacaoglu Yura Malitsky 51 61 0 16 Feb 2021
Linearly Converging Error Compensated SGD Eduard A. Gorbunov D. Kovalev Dmitry Makarenko Peter Richtárik 152 77 0 23 Oct 2020