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

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....

Celý popis

Podrobná bibliografie

Vydáno v:	Journal of global optimization Ročník 87; číslo 2-4; s. 709 - 740
Hlavní autoři:	Wang, Zhongruo, Balasubramanian, Krishnakumar, Ma, Shiqian, Razaviyayn, Meisam
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York Springer US 01.11.2023 Springer
Témata:	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
ISSN:	0925-5001, 1573-2916
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!