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Oct 31, 2022 · AG-OG is the first single-call algorithm with optimal convergence rates in both deterministic and stochastic settings for bilinearly coupled ...
AG-OG is the first single-call algorithm with optimal conver- gence rates in both deterministic and stochastic settings for bilinearly coupled minimax optimiza-.
Abstract. We provide a novel first-order optimization algorithm for bilinearly-coupled strongly-convex-concave minimax optimization called the ...
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Nov 23, 2022 · Abstract: We provide a novel first-order optimization algorithm for bilinearly-coupled strongly-convex-concave minimax optimization called ...
We provide a novel first-order optimization algorithm for bilinearly-coupled strongly-convex-concave minimax optimization called the AcceleratedGradient ...
Nesterov Meets Optimism: Rate-Optimal Optimistic-Gradient-Based Method for Stochastic Bilinearly-Coupled Minimax Optimization. Chris Junchi Li · Angela Yuan ...
Jul 23, 2023 · The main idea of our algorithm is to carefully leverage the structure of the minimax problem, performing Nesterov acceleration on the individual ...
Abstract. We propose a new first-order optimization algorithm—Accelerated-Gradient OptimisticGra- dient (AG-OG) Descent Ascent—for separable.
Abstract. We provide a novel first-order optimization algorithm for bilinearly-coupled strongly-convex-concave minimax optimization called the ...
AG-OG is the first single-call algorithm with optimal convergence rates in both deterministic and stochastic settings for bilinearly coupled minimax