A first-order augmented Lagrangian method for constrained minimax optimization
Optimization and Control
2024-10-29 v3 Machine Learning
Numerical Analysis
Numerical Analysis
Machine Learning
Abstract
In this paper we study a class of constrained minimax problems. In particular, we propose a first-order augmented Lagrangian method for solving them, whose subproblems turn out to be a much simpler structured minimax problem and are suitably solved by a first-order method developed in this paper. Under some suitable assumptions, an \emph{operation complexity} of , measured by its fundamental operations, is established for the first-order augmented Lagrangian method for finding an -KKT solution of the constrained minimax problems.
Cite
@article{arxiv.2301.02060,
title = {A first-order augmented Lagrangian method for constrained minimax optimization},
author = {Zhaosong Lu and Sanyou Mei},
journal= {arXiv preprint arXiv:2301.02060},
year = {2024}
}
Comments
Accepted by Mathematical Programming