The Limit Points of (Optimistic) Gradient Descent in Min-Max Optimization

11 July 2018

Papers citing "The Limit Points of (Optimistic) Gradient Descent in Min-Max Optimization"

11 / 11 papers shown

Title
Two-Timescale Gradient Descent Ascent Algorithms for Nonconvex Minimax Optimization Tianyi Lin Chi Jin Michael I. Jordan 77 8 0 28 Jan 2025
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 70 6 0 15 Jun 2024
Generating Less Certain Adversarial Examples Improves Robust Generalization Minxing Zhang Michael Backes Xiao Zhang AAML 76 1 0 06 Oct 2023
Poincaré Recurrence, Cycles and Spurious Equilibria in Gradient-Descent-Ascent for Non-Convex Non-Concave Zero-Sum Games Lampros Flokas Emmanouil-Vasileios Vlatakis-Gkaragkounis Georgios Piliouras MLT 48 41 0 28 Oct 2019
Training GANs with Optimism C. Daskalakis Andrew Ilyas Vasilis Syrgkanis Haoyang Zeng 95 514 0 31 Oct 2017
First-order Methods Almost Always Avoid Saddle Points Jason D. Lee Ioannis Panageas Georgios Piliouras Max Simchowitz Michael I. Jordan Benjamin Recht ODL 114 83 0 20 Oct 2017
Cycles in adversarial regularized learning P. Mertikopoulos Christos H. Papadimitriou Georgios Piliouras 29 319 0 08 Sep 2017
Gradient descent GAN optimization is locally stable Vaishnavh Nagarajan J. Zico Kolter GAN 62 348 0 13 Jun 2017
Local Maxima in the Likelihood of Gaussian Mixture Models: Structural Results and Algorithmic Consequences Chi Jin Yuchen Zhang Sivaraman Balakrishnan Martin J. Wainwright Michael I. Jordan 61 131 0 04 Sep 2016
Gradient Descent Only Converges to Minimizers: Non-Isolated Critical Points and Invariant Regions Ioannis Panageas Georgios Piliouras 41 141 0 02 May 2016
Online Learning with Predictable Sequences Alexander Rakhlin Karthik Sridharan 112 355 0 18 Aug 2012