12 papers
Single-Loop Stochastic Projected Damped Extragradient Methods for Nonconvex--(Strongly) Concave Minimax Optimization
Huiling Zhang, Minhao Zhang, Zi Xu +1
We develop single-loop stochastic projected damped extragradient methods for nonconvex--(strongly) concave minimax optimization, with complexity guarantees for both game stationari…
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 Oracle-Efficient Methods for Strongly Convex Composite Optimization
Xinming Wu, Zi Xu, Huiling Zhang
We consider strongly convex composite optimization problems whose objective is the sum of a general smooth component, a general nonsmooth component, and a relatively simple nonsmoo…
BEACON: Bayesian Optimal Stopping for Efficient LLM Sampling
Guangya Wan, Zixin Stephen Xu, Sasa Zorc +4
Sampling multiple responses is a common way to improve LLM output quality, but it comes at the cost of additional computation. The key challenge is deciding when to stop generating…
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.…
Two trust region type algorithms for solving nonconvex-strongly concave minimax problems
Tongliang Yao, Zi Xu
In this paper, we propose a Minimax Trust Region (MINIMAX-TR) algorithm and a Minimax Trust Region Algorithm with Contractions and Expansions(MINIMAX-TRACE) algorithm for solving n…
Zeroth-Order primal-dual Alternating Projection Gradient Algorithms for Nonconvex Minimax Problems with Coupled linear Constraints
Huiling Zhang, Zi Xu, Yuhong Dai
In this paper, we study zeroth-order algorithms for nonconvex minimax problems with coupled linear constraints under the deterministic and stochastic settings, which have attracted…
An accelerated first-order regularized momentum descent ascent algorithm for stochastic nonconvex-concave minimax problems
Huiling Zhang, Zi Xu
Stochastic nonconvex minimax problems have attracted wide attention in machine learning, signal processing and many other fields in recent years. In this paper, we propose an accel…
Derivative-free Alternating Projection Algorithms for General Nonconvex-Concave Minimax Problems
Zi Xu, Ziqi Wang, Jingjing Shen +1
In this paper, we study zeroth-order algorithms for nonconvex-concave minimax problems, which have attracted widely attention in machine learning, signal processing and many other…