Training GANs with Optimism

31 October 2017

Papers citing "Training GANs with Optimism"

50 / 102 papers shown

Title
Negative Stepsizes Make Gradient-Descent-Ascent Converge Henry Shugart Jason M. Altschuler 30 0 0 02 May 2025
Adversarial Locomotion and Motion Imitation for Humanoid Policy Learning Jiyuan Shi Xinzhe Liu Dewei Wang Ouyang Lu Sören Schwertfeger Fuchun Sun Chenjia Bai X. Li 47 0 0 19 Apr 2025
Learning Variational Inequalities from Data: Fast Generalization Rates under Strong Monotonicity Eric Zhao Tatjana Chavdarova Michael I. Jordan 50 0 0 20 Feb 2025
Two-Timescale Gradient Descent Ascent Algorithms for Nonconvex Minimax Optimization Tianyi Lin Chi Jin Michael I. Jordan 52 7 0 28 Jan 2025
Solving Infinite-Player Games with Player-to-Strategy Networks Carlos Martin T. Sandholm 59 0 0 17 Jan 2025
Non-Adversarial Inverse Reinforcement Learning via Successor Feature Matching A. Jain Harley Wiltzer Jesse Farebrother Irina Rish Glen Berseth Sanjiban Choudhury 57 1 0 11 Nov 2024
Contractivity and linear convergence in bilinear saddle-point problems: An operator-theoretic approach Colin Dirren Mattia Bianchi Panagiotis D. Grontas John Lygeros Florian Dorfler 36 0 0 18 Oct 2024
Multiple Greedy Quasi-Newton Methods for Saddle Point Problems Minheng Xiao Shi Bo Zhizhong Wu 30 5 0 01 Aug 2024
Accelerated Stochastic Min-Max Optimization Based on Bias-corrected Momentum H. Cai Sulaiman A. Alghunaim Ali H.Sayed 52 1 0 18 Jun 2024
Fast Last-Iterate Convergence of Learning in Games Requires Forgetful Algorithms Yang Cai Gabriele Farina Julien Grand-Clément Christian Kroer Chung-Wei Lee Haipeng Luo Weiqiang Zheng 58 6 0 15 Jun 2024
Universal randomised signatures for generative time series modelling Francesca Biagini Lukas Gonon Niklas Walter 42 4 0 14 Jun 2024
Primal Methods for Variational Inequality Problems with Functional Constraints Liang Zhang Niao He Michael Muehlebach 42 2 0 19 Mar 2024
Dealing with unbounded gradients in stochastic saddle-point optimization Gergely Neu Nneka Okolo 37 3 0 21 Feb 2024
Aligning Individual and Collective Objectives in Multi-Agent Cooperation Yang Li Wenhao Zhang Jianhong Wang Shao Zhang Yali Du Ying Wen Wei Pan 26 1 0 19 Feb 2024
Momentum-SAM: Sharpness Aware Minimization without Computational Overhead Marlon Becker Frederick Altrock Benjamin Risse 82 5 0 22 Jan 2024
A Minimaximalist Approach to Reinforcement Learning from Human Feedback Gokul Swamy Christoph Dann Rahul Kidambi Zhiwei Steven Wu Alekh Agarwal OffRL 41 96 0 08 Jan 2024
Last-Iterate Convergence Properties of Regret-Matching Algorithms in Games Yang Cai Gabriele Farina Julien Grand-Clément Christian Kroer Chung-Wei Lee Haipeng Luo Weiqiang Zheng 28 1 0 01 Nov 2023
Multi-Player Zero-Sum Markov Games with Networked Separable Interactions Chanwoo Park Kaipeng Zhang Asuman Ozdaglar 30 8 0 13 Jul 2023
Data Interpolants -- That's What Discriminators in Higher-order Gradient-regularized GANs Are Siddarth Asokan C. Seelamantula 32 4 0 01 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 46 14 0 25 May 2023
Estimation Beyond Data Reweighting: Kernel Method of Moments Heiner Kremer Yassine Nemmour Bernhard Schölkopf Jia-Jie Zhu 36 7 0 18 May 2023
Sublinear Convergence Rates of Extragradient-Type Methods: A Survey on Classical and Recent Developments Quoc Tran-Dinh 35 7 0 30 Mar 2023
Inverse Reinforcement Learning without Reinforcement Learning Gokul Swamy Sanjiban Choudhury J. Andrew Bagnell Zhiwei Steven Wu 21 34 0 26 Mar 2023
Can We Find Nash Equilibria at a Linear Rate in Markov Games? Zhuoqing Song Jason D. Lee Zhuoran Yang 29 8 0 03 Mar 2023
Similarity, Compression and Local Steps: Three Pillars of Efficient Communications for Distributed Variational Inequalities Aleksandr Beznosikov Martin Takáč Alexander Gasnikov 31 10 0 15 Feb 2023
Minimax Instrumental Variable Regression and $L_2$ Convergence Guarantees without Identification or Closedness Andrew Bennett Nathan Kallus Xiaojie Mao Whitney Newey Vasilis Syrgkanis Masatoshi Uehara 36 14 0 10 Feb 2023
Learning in Multi-Memory Games Triggers Complex Dynamics Diverging from Nash Equilibrium Yuma Fujimoto Kaito Ariu Kenshi Abe 28 4 0 02 Feb 2023
Primal Dual Alternating Proximal Gradient Algorithms for Nonsmooth Nonconvex Minimax Problems with Coupled Linear Constraints Hui-Li Zhang Junlin Wang Zi Xu Y. Dai 88 4 0 09 Dec 2022
Blessings and Curses of Covariate Shifts: Adversarial Learning Dynamics, Directional Convergence, and Equilibria Tengyuan Liang 22 1 0 05 Dec 2022
Finding mixed-strategy equilibria of continuous-action games without gradients using randomized policy networks Carlos Martin T. Sandholm 34 11 0 29 Nov 2022
Zeroth-Order Alternating Gradient Descent Ascent Algorithms for a Class of Nonconvex-Nonconcave Minimax Problems Zi Xu Ziqi Wang Junlin Wang Y. Dai 21 11 0 24 Nov 2022
TiAda: A Time-scale Adaptive Algorithm for Nonconvex Minimax Optimization Xiang Li Junchi Yang Niao He 26 8 0 31 Oct 2022
Explicit Second-Order Min-Max Optimization Methods with Optimal Convergence Guarantee Tianyi Lin P. Mertikopoulos Michael I. Jordan 26 11 0 23 Oct 2022
Accelerated Single-Call Methods for Constrained Min-Max Optimization Yang Cai Weiqiang Zheng 27 30 0 06 Oct 2022
Last-Iterate Convergence with Full and Noisy Feedback in Two-Player Zero-Sum Games Kenshi Abe Kaito Ariu Mitsuki Sakamoto Kenta Toyoshima Atsushi Iwasaki 34 11 0 21 Aug 2022
The Power of Regularization in Solving Extensive-Form Games Ming Liu Asuman Ozdaglar Tiancheng Yu Kaipeng Zhang 24 20 0 19 Jun 2022
On Scaled Methods for Saddle Point Problems Aleksandr Beznosikov Aibek Alanov D. Kovalev Martin Takáč Alexander Gasnikov 30 4 0 16 Jun 2022
Alternating Mirror Descent for Constrained Min-Max Games Andre Wibisono Molei Tao Georgios Piliouras 29 14 0 08 Jun 2022
Minimax Optimal Online Imitation Learning via Replay Estimation Gokul Swamy Nived Rajaraman Matt Peng Sanjiban Choudhury J. Andrew Bagnell Zhiwei Steven Wu Jiantao Jiao Kannan Ramchandran OffRL 29 18 0 30 May 2022
HessianFR: An Efficient Hessian-based Follow-the-Ridge Algorithm for Minimax Optimization Yihang Gao Huafeng Liu Michael K. Ng Mingjie Zhou 25 2 0 23 May 2022
Distributed Statistical Min-Max Learning in the Presence of Byzantine Agents Arman Adibi A. Mitra George J. Pappas Hamed Hassani 29 3 0 07 Apr 2022
Federated Minimax Optimization: Improved Convergence Analyses and Algorithms Pranay Sharma Rohan Panda Gauri Joshi P. Varshney FedML 21 47 0 09 Mar 2022
Semi-Implicit Hybrid Gradient Methods with Application to Adversarial Robustness Beomsu Kim Junghoon Seo AAML 22 0 0 21 Feb 2022
Optimal Algorithms for Decentralized Stochastic Variational Inequalities D. Kovalev Aleksandr Beznosikov Abdurakhmon Sadiev Michael Persiianov Peter Richtárik Alexander Gasnikov 35 35 0 06 Feb 2022
Learning for Robust Combinatorial Optimization: Algorithm and Application Zhihui Shao Jianyi Yang Cong Shen Shaolei Ren 38 6 0 20 Dec 2021
No-Regret Dynamics in the Fenchel Game: A Unified Framework for Algorithmic Convex Optimization Jun-Kun Wang Jacob D. Abernethy Kfir Y. Levy 27 21 0 22 Nov 2021
Second-Order Mirror Descent: Convergence in Games Beyond Averaging and Discounting Bolin Gao Lacra Pavel 25 8 0 18 Nov 2021
Near-Optimal No-Regret Learning for Correlated Equilibria in Multi-Player General-Sum Games Ioannis Anagnostides C. Daskalakis Gabriele Farina Maxwell Fishelson Noah Golowich T. Sandholm 62 53 0 11 Nov 2021
Uncoupled Bandit Learning towards Rationalizability: Benchmarks, Barriers, and Algorithms Jibang Wu Haifeng Xu Fan Yao 30 1 0 10 Nov 2021
Minimax Optimization: The Case of Convex-Submodular Arman Adibi Aryan Mokhtari Hamed Hassani 21 7 0 01 Nov 2021