10 citations · 17 across the 24 of their papers we have counts for
5 papers · 1 filter
Accelerating Min-Max Optimization via Power-Law Stepsizes
Yue Wu, Weiqiang Zheng, Yang Cai +1
We revisit the convergence guarantees of the Extragradient (EG) method for unconstrained biaffine min-max optimization. It is known that EG with a fixed stepsize achieves a $Θ(T^{-…
Last-Iterate Convergence of Anchored Gradient Descent
Yang Cai, Weiqiang Zheng
We study the monotone inclusion problem , where is monotone and Lipschitz, and is maximally monotone, a framework that encompasses monotone variational ineq…
Accelerated Single-Call Methods for Constrained Min-Max Optimization
Yang Cai, Weiqiang Zheng
We study first-order methods for constrained min-max optimization. Existing methods either require two gradient calls or two projections in each iteration, which may be costly in s…
Accelerated Algorithms for Constrained Nonconvex-Nonconcave Min-Max Optimization and Comonotone Inclusion
Yang Cai, Argyris Oikonomou, Weiqiang Zheng
We study constrained comonotone min-max optimization, a structured class of nonconvex-nonconcave min-max optimization problems, and their generalization to comonotone inclusion. In…
Tight Last-Iterate Convergence of the Extragradient and the Optimistic Gradient Descent-Ascent Algorithm for Constrained Monotone Variational Inequalities
Yang Cai, Argyris Oikonomou, Weiqiang Zheng
The monotone variational inequality is a central problem in mathematical programming that unifies and generalizes many important settings such as smooth convex optimization, two-pl…