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saddle-point problems

19 papers

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Co-occurring keywords

convex optimization (1321) variational inequality (48) stochastic optimization (1060) linear convergence (158) zero-sum game (190) primal-dual method (58) extragradient method (17) generative adversarial network (1944) min-max optimization (80) monotone operator (18)

Papers

Mirror Descent Algorithms with Nearly Dimension-Independent Rates for Differentially-Private Stochastic Saddle-Point Problems extended abstract COLT 2024
Stochastic Approximation Approaches to Group Distributionally Robust Optimization NIPS 2023
Optimal Extragradient-Based Algorithms for Stochastic Variational Inequalities with Separable Structure NIPS 2023
Communication Acceleration of Local Gradient Methods via an Accelerated Primal-Dual Algorithm with an Inexact Prox NIPS 2022
Accelerated Primal-Dual Gradient Method for Smooth and Convex-Concave Saddle-Point Problems with Bilinear Coupling NIPS 2022
A Unifying Framework for Variance-Reduced Algorithms for Findings Zeroes of Monotone operators JMLR 2022
Conic Blackwell Algorithm: Parameter-Free Convex-Concave Saddle-Point Solving NIPS 2021
Increasing Iterate Averaging for Solving Saddle-Point Problems AAAI 2021
First-order Convergence Theory for Weakly-Convex-Weakly-Concave Min-max Problems JMLR 2021
Distributed Saddle-Point Problems Under Data Similarity NIPS 2021
Variational Bayesian Optimistic Sampling NIPS 2021
Explore Aggressively, Update Conservatively: Stochastic Extragradient Methods with Variable Stepsize Scaling NIPS 2020
Dual Instrumental Variable Regression NIPS 2020
Linear Lower Bounds and Conditioning of Differentiable Games ICML 2020
Revisiting Stochastic Extragradient AISTATS 2020
Multi-Agent Reinforcement Learning via Double Averaging Primal-Dual Optimization NIPS 2018
Stochastic Variance Reduction Methods for Policy Evaluation ICML 2017
Stochastic Variance Reduction Methods for Saddle-Point Problems NIPS 2016
Optimization, Learning, and Games with Predictable Sequences NIPS 2013