Reducing Noise in GAN Training with Variance Reduced Extragradient

18 April 2019

Papers citing "Reducing Noise in GAN Training with Variance Reduced Extragradient"

27 / 27 papers shown

Title
Multiple Greedy Quasi-Newton Methods for Saddle Point Problems Minheng Xiao Shi Bo Zhizhong Wu 30 5 0 01 Aug 2024
Stochastic Halpern iteration in normed spaces and applications to reinforcement learning Mario Bravo Juan Pablo Contreras 40 3 0 19 Mar 2024
First Order Methods with Markovian Noise: from Acceleration to Variational Inequalities Aleksandr Beznosikov S. Samsonov Marina Sheshukova Alexander Gasnikov A. Naumov Eric Moulines 32 14 0 25 May 2023
Similarity, Compression and Local Steps: Three Pillars of Efficient Communications for Distributed Variational Inequalities Aleksandr Beznosikov Martin Takáč Alexander Gasnikov 26 10 0 15 Feb 2023
SARAH-based Variance-reduced Algorithm for Stochastic Finite-sum Cocoercive Variational Inequalities Aleksandr Beznosikov Alexander Gasnikov 25 2 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 37 31 0 29 Aug 2022
On Scaled Methods for Saddle Point Problems Aleksandr Beznosikov Aibek Alanov D. Kovalev Martin Takáč Alexander Gasnikov 22 4 0 16 Jun 2022
Semi-Implicit Hybrid Gradient Methods with Application to Adversarial Robustness Beomsu Kim Junghoon Seo AAML 20 0 0 21 Feb 2022
Stochastic Gradient Descent-Ascent: Unified Theory and New Efficient Methods Aleksandr Beznosikov Eduard A. Gorbunov Hugo Berard Nicolas Loizou 19 47 0 15 Feb 2022
Optimal Algorithms for Decentralized Stochastic Variational Inequalities D. Kovalev Aleksandr Beznosikov Abdurakhmon Sadiev Michael Persiianov Peter Richtárik Alexander Gasnikov 35 34 0 06 Feb 2022
Decentralized Stochastic Variance Reduced Extragradient Method Luo Luo Haishan Ye 16 7 0 01 Feb 2022
Stochastic Extragradient: General Analysis and Improved Rates Eduard A. Gorbunov Hugo Berard Gauthier Gidel Nicolas Loizou 14 40 0 16 Nov 2021
Extragradient Method: $O(1/K)$ Last-Iterate Convergence for Monotone Variational Inequalities and Connections With Cocoercivity Eduard A. Gorbunov Nicolas Loizou Gauthier Gidel 23 64 0 08 Oct 2021
Decentralized Local Stochastic Extra-Gradient for Variational Inequalities Aleksandr Beznosikov Pavel Dvurechensky Anastasia Koloskova V. Samokhin Sebastian U. Stich Alexander Gasnikov 26 43 0 15 Jun 2021
The Complexity of Nonconvex-Strongly-Concave Minimax Optimization Siqi Zhang Junchi Yang Cristóbal Guzmán Negar Kiyavash Niao He 31 60 0 29 Mar 2021
Training Generative Adversarial Networks by Solving Ordinary Differential Equations Chongli Qin Yan Wu Jost Tobias Springenberg Andrew Brock Jeff Donahue Timothy Lillicrap Pushmeet Kohli GAN 22 28 0 28 Oct 2020
Adaptive extra-gradient methods for min-max optimization and games Kimon Antonakopoulos E. V. Belmega P. Mertikopoulos 54 46 0 22 Oct 2020
Adaptive and Universal Algorithms for Variational Inequalities with Optimal Convergence Alina Ene Huy Le Nguyen 12 13 0 15 Oct 2020
Stochastic Hamiltonian Gradient Methods for Smooth Games Nicolas Loizou Hugo Berard Alexia Jolicoeur-Martineau Pascal Vincent Simon Lacoste-Julien Ioannis Mitliagkas 31 50 0 08 Jul 2020
Empirical Analysis of Overfitting and Mode Drop in GAN Training Yasin Yazici Chuan-Sheng Foo Stefan Winkler Kim-Hui Yap V. Chandrasekhar 24 29 0 25 Jun 2020
The limits of min-max optimization algorithms: convergence to spurious non-critical sets Ya-Ping Hsieh P. Mertikopoulos V. Cevher 27 81 0 16 Jun 2020
Towards Better Understanding of Adaptive Gradient Algorithms in Generative Adversarial Nets Mingrui Liu Youssef Mroueh Jerret Ross Wei Zhang Xiaodong Cui Payel Das Tianbao Yang ODL 30 63 0 26 Dec 2019
Small-GAN: Speeding Up GAN Training Using Core-sets Samarth Sinha Hang Zhang Anirudh Goyal Yoshua Bengio Hugo Larochelle Augustus Odena GAN 22 72 0 29 Oct 2019
ODE Analysis of Stochastic Gradient Methods with Optimism and Anchoring for Minimax Problems Ernest K. Ryu Kun Yuan W. Yin 17 36 0 26 May 2019
Cocoercivity, Smoothness and Bias in Variance-Reduced Stochastic Gradient Methods Martin Morin Pontus Giselsson 15 2 0 21 Mar 2019
A Unified Analysis of Extra-gradient and Optimistic Gradient Methods for Saddle Point Problems: Proximal Point Approach Aryan Mokhtari Asuman Ozdaglar S. Pattathil 17 323 0 24 Jan 2019
A Proximal Stochastic Gradient Method with Progressive Variance Reduction Lin Xiao Tong Zhang ODL 84 736 0 19 Mar 2014