A J-symmetric quasi-newton method for minimax problems

Minimax problems have gained tremendous attentions across the optimization and machine learning community recently. In this paper, we introduce a new quasi-Newton method for the minimax problems, which we call J -symmetric quasi-Newton method. The method is obtained by exploiting the J -symmetric st...

Full description

Saved in:

Bibliographic Details
Published in:	Mathematical programming Vol. 204; no. 1-2; pp. 207 - 254
Main Authors:	Asl, Azam, Lu, Haihao, Yang, Jinwen
Format:	Journal Article
Language:	English
Published:	Berlin/Heidelberg Springer Berlin Heidelberg 01.03.2024 Springer
Subjects:	Algorithms Calculus of Variations and Optimal Control; Optimization Combinatorics Full Length Paper Machine learning Mathematical and Computational Physics Mathematical Methods in Physics Mathematics Mathematics and Statistics Mathematics of Computing Methods Numerical Analysis Theoretical 65K15 Quasi-Newton method Trust region 90C47 Minimax optimization Superlinear convergence symmetric 49K35
ISSN:	0025-5610, 1436-4646
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!