Zeroth-order algorithms for nonconvex–strongly-concave minimax problems with improved complexities

• Published in: Journal of global optimization Vol. 87; no. 2-4; pp. 709 - 740
• Main Authors: Wang, Zhongruo, Balasubramanian, Krishnakumar, Ma, Shiqian, Razaviyayn, Meisam
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.11.2023; Springer
• Subjects: Algorithms; Comparative analysis; Computer Science; Machine learning; Mathematics; Mathematics and Statistics; Operations Research/Decision Theory; Optimization; Real Functions; Stochastic algorithms; Oracle complexity; Gradient descent ascent; Minimax problem; Zeroth-order algorithms

In this paper, we study zeroth-order algorithms for minimax optimization problems that are nonconvex in one variable and strongly-concave in the other variable. Such minimax optimization problems have attracted significant attention lately due to their applications in modern machine learning tasks....