9 papers · 1 filter
A Homogeneous Second-Order Descent Ascent Algorithm for Nonconvex-Strongly Concave Minimax Problems
Jia-Hao Chen, Zi Xu, Hui-Ling Zhang
This paper introduces a novel Homogeneous Second-order Descent Ascent (HSDA) algorithm for nonconvex-strongly concave minimax optimization problems. At each iteration, HSDA uniquel…
Restart-Free (Accelerated) Gradient Sliding Methods for Strongly Convex Composite Optimization
Xinming Wu, Zi Xu, Huiling Zhang
In this paper, we study a class of composite optimization problems whose objective function is given by the summation of a general smooth and nonsmooth component, together with a r…
Gradient Norm Regularization Second-Order Algorithms for Solving Nonconvex-Strongly Concave Minimax Problems
Jun-Lin Wang, Zi Xu
In this paper, we study second-order algorithms for solving nonconvex-strongly concave minimax problems, which have attracted much attention in recent years in many fields, especia…
Zeroth-Order Stochastic Mirror Descent Algorithms for Minimax Excess Risk Optimization
Zhihao Gu, Zi Xu
The minimax excess risk optimization (MERO) problem is a new variation of the traditional distributionally robust optimization (DRO) problem, which achieves uniformly low regret ac…
Completely Parameter-Free Single-Loop Algorithms for Nonconvex-Concave Minimax Problems
Junnan Yang, Huiling Zhang, Zi Xu
Due to their importance in various emerging applications, efficient algorithms for solving minimax problems have recently received increasing attention. However, many existing algo…
A Fully Parameter-Free Second-Order Algorithm for Convex-Concave Minimax Problems
Junlin Wang, Zi Xu, Huiling Zhang
In this paper, we study second-order algorithms for the convex-concave minimax problem, which has attracted much attention in many fields such as machine learning in recent years.…