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Optimal Algorithms for Decentralized Stochastic Variational Inequalities

6 February 2022

Alexander Gasnikov

Papers citing "Optimal Algorithms for Decentralized Stochastic Variational Inequalities"

33 / 33 papers shown

Title
Stochastic Gradient Descent-Ascent: Unified Theory and New Efficient Methods Aleksandr Beznosikov Eduard A. Gorbunov Hugo Berard Nicolas Loizou 67 50 0 15 Feb 2022
Decentralized Local Stochastic Extra-Gradient for Variational Inequalities Aleksandr Beznosikov Pavel Dvurechensky Anastasia Koloskova V. Samokhin Sebastian U. Stich Alexander Gasnikov 56 43 0 15 Jun 2021
A Decentralized Adaptive Momentum Method for Solving a Class of Min-Max Optimization Problems Babak Barazandeh Tianjian Huang George Michailidis 65 12 0 10 Jun 2021
Lower Bounds and Optimal Algorithms for Smooth and Strongly Convex Decentralized Optimization Over Time-Varying Networks D. Kovalev Elnur Gasanov Peter Richtárik Alexander Gasnikov 51 44 0 08 Jun 2021
Accelerated Gradient Tracking over Time-varying Graphs for Decentralized Optimization Huan Li Zhouchen Lin 32 33 0 06 Apr 2021
Stochastic Variance Reduction for Variational Inequality Methods Ahmet Alacaoglu Yura Malitsky 75 71 0 16 Feb 2021
Efficiently Solving MDPs with Stochastic Mirror Descent Yujia Jin Aaron Sidford 54 71 0 28 Aug 2020
Optimal and Practical Algorithms for Smooth and Strongly Convex Decentralized Optimization D. Kovalev Adil Salim Peter Richtárik 43 83 0 21 Jun 2020
An Optimal Algorithm for Decentralized Finite Sum Optimization Hadrien Hendrikx Francis R. Bach Laurent Massoulie 55 45 0 20 May 2020
A Unified Theory of Decentralized SGD with Changing Topology and Local Updates Anastasia Koloskova Nicolas Loizou Sadra Boreiri Martin Jaggi Sebastian U. Stich FedML 85 514 0 23 Mar 2020
Global Convergence and Variance-Reduced Optimization for a Class of Nonconvex-Nonconcave Minimax Problems Junchi Yang Negar Kiyavash Niao He 88 84 0 22 Feb 2020
Advances and Open Problems in Federated Learning Peter Kairouz H. B. McMahan Brendan Avent A. Bellet M. Bennis ... Zheng Xu Qiang Yang Felix X. Yu Han Yu Sen Zhao FedML AI4CE 259 6,276 0 10 Dec 2019
A Decentralized Parallel Algorithm for Training Generative Adversarial Nets Mingrui Liu Wei Zhang Youssef Mroueh Xiaodong Cui Jerret Ross Tianbao Yang Payel Das 48 74 0 28 Oct 2019
FreeLB: Enhanced Adversarial Training for Natural Language Understanding Chen Zhu Yu Cheng Zhe Gan S. Sun Tom Goldstein Jingjing Liu AAML 272 442 0 25 Sep 2019
On the convergence of single-call stochastic extra-gradient methods Yu-Guan Hsieh F. Iutzeler J. Malick P. Mertikopoulos 59 169 0 22 Aug 2019
Variance Reduction for Matrix Games Y. Carmon Yujia Jin Aaron Sidford Kevin Tian 67 67 0 03 Jul 2019
Reducing Noise in GAN Training with Variance Reduced Extragradient Tatjana Chavdarova Gauthier Gidel François Fleuret Simon Lacoste-Julien 58 137 0 18 Apr 2019
Large Batch Optimization for Deep Learning: Training BERT in 76 minutes Yang You Jing Li Sashank J. Reddi Jonathan Hseu Sanjiv Kumar Srinadh Bhojanapalli Xiaodan Song J. Demmel Kurt Keutzer Cho-Jui Hsieh ODL 251 999 0 01 Apr 2019
Training GANs with Centripetal Acceleration Wei Peng Yuhong Dai Hui Zhang Lizhi Cheng GAN 58 43 0 24 Feb 2019
Large Scale GAN Training for High Fidelity Natural Image Synthesis Andrew Brock Jeff Donahue Karen Simonyan 269 5,401 0 28 Sep 2018
Optimistic mirror descent in saddle-point problems: Going the extra (gradient) mile P. Mertikopoulos Bruno Lecouat Houssam Zenati Chuan-Sheng Foo V. Chandrasekhar Georgios Piliouras 135 297 0 07 Jul 2018
A Variational Inequality Perspective on Generative Adversarial Networks Gauthier Gidel Hugo Berard Gaëtan Vignoud Pascal Vincent Simon Lacoste-Julien GAN 138 353 0 28 Feb 2018
Interaction Matters: A Note on Non-asymptotic Local Convergence of Generative Adversarial Networks Tengyuan Liang J. Stokes 109 212 0 16 Feb 2018
Training GANs with Optimism C. Daskalakis Andrew Ilyas Vasilis Syrgkanis Haoyang Zeng 175 519 0 31 Oct 2017
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 310 12,117 0 19 Jun 2017
Deep Decentralized Multi-task Multi-Agent Reinforcement Learning under Partial Observability Shayegan Omidshafiei Jason Pazis Chris Amato Jonathan P. How J. Vian 132 498 0 17 Mar 2017
Optimal algorithms for smooth and strongly convex distributed optimization in networks Kevin Scaman Francis R. Bach Sébastien Bubeck Y. Lee Laurent Massoulié 74 331 0 28 Feb 2017
Federated Learning: Strategies for Improving Communication Efficiency Jakub Konecný H. B. McMahan Felix X. Yu Peter Richtárik A. Suresh Dave Bacon FedML 306 4,649 0 18 Oct 2016
Stochastic Variance Reduction Methods for Saddle-Point Problems B. Palaniappan Francis R. Bach 124 214 0 20 May 2016
Communication-Efficient Learning of Deep Networks from Decentralized Data H. B. McMahan Eider Moore Daniel Ramage S. Hampson Blaise Agüera y Arcas FedML 406 17,559 0 17 Feb 2016
Optimization with Sparsity-Inducing Penalties Francis R. Bach Rodolphe Jenatton Julien Mairal G. Obozinski 216 1,058 0 03 Aug 2011
Convex Sparse Matrix Factorizations Francis R. Bach Julien Mairal Jean Ponce 193 143 0 10 Dec 2008
Solving variational inequalities with Stochastic Mirror-Prox algorithm A. Juditsky A. Nemirovskii Claire Tauvel 137 443 0 04 Sep 2008