Sharper Rates for Separable Minimax and Finite Sum Optimization via Primal-Dual Extragradient Methods

9 February 2022

Papers citing "Sharper Rates for Separable Minimax and Finite Sum Optimization via Primal-Dual Extragradient Methods"

39 / 39 papers shown

Title
Generative Adversarial Networks Gilad Cohen Raja Giryes GAN 301 30,152 0 01 Mar 2022
Lifted Primal-Dual Method for Bilinearly Coupled Smooth Minimax Optimization K. K. Thekumparampil Niao He Sewoong Oh 76 30 0 19 Jan 2022
Accelerated Primal-Dual Gradient Method for Smooth and Convex-Concave Saddle-Point Problems with Bilinear Coupling D. Kovalev Alexander Gasnikov Peter Richtárik 117 33 0 30 Dec 2021
Variance Reduction via Primal-Dual Accelerated Dual Averaging for Nonsmooth Convex Finite-Sums Chaobing Song Stephen J. Wright Jelena Diakonikolas 119 17 0 26 Feb 2021
Stochastic Variance Reduction for Variational Inequality Methods Ahmet Alacaoglu Yura Malitsky 93 71 0 16 Feb 2021
Relative Lipschitzness in Extragradient Methods and a Direct Recipe for Acceleration Michael B. Cohen Aaron Sidford Kevin Tian 67 41 0 12 Nov 2020
Coordinate Methods for Matrix Games Y. Carmon Yujia Jin Aaron Sidford Kevin Tian 55 33 0 17 Sep 2020
Random extrapolation for primal-dual coordinate descent Ahmet Alacaoglu Olivier Fercoq Volkan Cevher 48 17 0 13 Jul 2020
Optimal and Practical Algorithms for Smooth and Strongly Convex Decentralized Optimization D. Kovalev Adil Salim Peter Richtárik 56 83 0 21 Jun 2020
Variance Reduction via Accelerated Dual Averaging for Finite-Sum Optimization Chaobing Song Yong Jiang Yi-An Ma 118 23 0 18 Jun 2020
Improved Algorithms for Convex-Concave Minimax Optimization Yuanhao Wang Jian Li 80 64 0 11 Jun 2020
Halpern Iteration for Near-Optimal and Parameter-Free Monotone Inclusion and Strong Solutions to Variational Inequalities Jelena Diakonikolas 67 77 0 20 Feb 2020
Near-Optimal Algorithms for Minimax Optimization Tianyi Lin Chi Jin Michael I. Jordan 201 254 0 05 Feb 2020
On the convergence of single-call stochastic extra-gradient methods Yu-Guan Hsieh F. Iutzeler J. Malick P. Mertikopoulos 69 169 0 22 Aug 2019
Variance Reduction for Matrix Games Y. Carmon Yujia Jin Aaron Sidford Kevin Tian 84 67 0 03 Jul 2019
A unified variance-reduced accelerated gradient method for convex optimization Guanghui Lan Zhize Li Yi Zhou 60 61 0 29 May 2019
Reducing Noise in GAN Training with Variance Reduced Extragradient Tatjana Chavdarova Gauthier Gidel François Fleuret Simon Lacoste-Julien 69 137 0 18 Apr 2019
Acceleration through Optimistic No-Regret Dynamics Jun-Kun Wang Jacob D. Abernethy 154 45 0 27 Jul 2018
Direct Acceleration of SAGA using Sampled Negative Momentum Kaiwen Zhou 92 45 0 28 Jun 2018
Faster Rates for Convex-Concave Games Jacob D. Abernethy Kevin A. Lai Kfir Y. Levy Jun-Kun Wang 26 47 0 17 May 2018
Leverage Score Sampling for Faster Accelerated Regression and ERM Naman Agarwal Sham Kakade Rahul Kidambi Y. Lee Praneeth Netrapalli Aaron Sidford 115 21 0 22 Nov 2017
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 319 12,151 0 19 Jun 2017
Stochastic Primal-Dual Hybrid Gradient Algorithm with Arbitrary Sampling and Imaging Applications A. Chambolle Matthias Joachim Ehrhardt Peter Richtárik Carola-Bibiane Schönlieb 102 187 0 15 Jun 2017
Exploiting Strong Convexity from Data with Primal-Dual First-Order Algorithms Jialei Wang Lin Xiao 119 42 0 07 Mar 2017
Stochastic Variance Reduction Methods for Policy Evaluation S. Du Jianshu Chen Lihong Li Lin Xiao Dengyong Zhou OffRL 63 158 0 25 Feb 2017
Optimization Methods for Large-Scale Machine Learning Léon Bottou Frank E. Curtis J. Nocedal 256 3,226 0 15 Jun 2016
Tight Complexity Bounds for Optimizing Composite Objectives Blake E. Woodworth Nathan Srebro 138 185 0 25 May 2016
Stochastic Variance Reduction Methods for Saddle-Point Problems B. Palaniappan Francis R. Bach 139 214 0 20 May 2016
Katyusha: The First Direct Acceleration of Stochastic Gradient Methods Zeyuan Allen-Zhu ODL 127 581 0 18 Mar 2016
Optimal Black-Box Reductions Between Optimization Objectives Zeyuan Allen-Zhu Elad Hazan 102 96 0 17 Mar 2016
A Simple Practical Accelerated Method for Finite Sums Aaron Defazio 145 121 0 08 Feb 2016
Even Faster Accelerated Coordinate Descent Using Non-Uniform Sampling Zeyuan Allen-Zhu Zheng Qu Peter Richtárik Yang Yuan 91 171 0 30 Dec 2015
Un-regularizing: approximate proximal point and faster stochastic algorithms for empirical risk minimization Roy Frostig Rong Ge Sham Kakade Aaron Sidford 74 150 0 24 Jun 2015
Stochastic Primal-Dual Coordinate Method for Regularized Empirical Risk Minimization Yuchen Zhang Xiao Lin 119 265 0 10 Sep 2014
SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives Aaron Defazio Francis R. Bach Simon Lacoste-Julien ODL 139 1,830 0 01 Jul 2014
Minimizing Finite Sums with the Stochastic Average Gradient Mark Schmidt Nicolas Le Roux Francis R. Bach 331 1,250 0 10 Sep 2013
Accelerated Proximal Stochastic Dual Coordinate Ascent for Regularized Loss Minimization Shai Shalev-Shwartz Tong Zhang ODL 115 463 0 10 Sep 2013
Stochastic Dual Coordinate Ascent Methods for Regularized Loss Minimization Shai Shalev-Shwartz Tong Zhang 198 1,033 0 10 Sep 2012
Solving variational inequalities with Stochastic Mirror-Prox algorithm A. Juditsky A. Nemirovskii Claire Tauvel 140 444 0 04 Sep 2008