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minimax optimization

186 papers

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Co-occurring keywords

nonconvex optimization (316) gradient descent ascent (31) stochastic optimization (1060) adversarial learning (1595) convex optimization (1321) stochastic gradient descent (1091) convergence rate (607) variance reduction (523) generative adversarial network (1944) gradient descent (1144)

Papers

Lifted Primal-Dual Method for Bilinearly Coupled Smooth Minimax Optimization AISTATS 2022
Tight Analysis of Extra-gradient and Optimistic Gradient Methods For Nonconvex Minimax Problems NIPS 2022
Accelerated Algorithms for Smooth Convex-Concave Minimax Problems with O(1/k^2) Rate on Squared Gradient Norm ICML 2021
Robust Reinforcement Learning: A Constrained Game-theoretic Approach L4DC 2021
Is Pessimism Provably Efficient for Offline RL? ICML 2021
Fast Extra Gradient Methods for Smooth Structured Nonconvex-Nonconcave Minimax Problems NIPS 2021
On the Convergence of Stochastic Compositional Gradient Descent Ascent Method IJCAI 2021
On the Suboptimality of Negative Momentum for Minimax Optimization AISTATS 2021
The complexity of nonconvex-strongly-concave minimax optimization UAI 2021
Adversarially robust learning for security-constrained optimal power flow NIPS 2021
Train simultaneously, generalize better: Stability of gradient-based minimax learners ICML 2021
Minimax Adaptive Control for a Finite Set of Linear Systems L4DC 2021
Minimax Optimal Quantile and Semi-Adversarial Regret via Root-Logarithmic Regularizers NIPS 2021
A Wasserstein Minimax Framework for Mixed Linear Regression ICML 2021
Combining Pessimism with Optimism for Robust and Efficient Model-Based Deep Reinforcement Learning ICML 2021
Local Stochastic Gradient Descent Ascent: Convergence Analysis and Communication Efficiency AISTATS 2021
Last iterate convergence in no-regret learning: constrained min-max optimization for convex-concave landscapes AISTATS 2021
A Faster Decentralized Algorithm for Nonconvex Minimax Problems NIPS 2021
Efficient Mirror Descent Ascent Methods for Nonsmooth Minimax Problems NIPS 2021
Uniform-PAC Bounds for Reinforcement Learning with Linear Function Approximation NIPS 2021
Optimal Minimax Variable Selection for Large-Scale Matrix Linear Regression Model JMLR 2021
Thinking Inside the Ball: Near-Optimal Minimization of the Maximal Loss COLT 2021
Minimax Model Learning AISTATS 2021
Achieving Near Instance-Optimality and Minimax-Optimality in Stochastic and Adversarial Linear Bandits Simultaneously ICML 2021
On the Optimality of Batch Policy Optimization Algorithms ICML 2021