Oct 23, 2022 · Explicit Second-Order Min-Max Optimization Methods with Optimal Convergence Guarantee. Authors:Tianyi Lin, Panayotis Mertikopoulos, Michael I.
Nov 18, 2022 · In this section, we present the scheme of Newton-MinMax and establish a global convergence rate guarantee. Moreover, we provide intuition into ...
Sep 6, 2023 · In this paper, we examine how second-order information can be used to speed up extra-gradient methods, even under inexactness. Specifically, we ...
Nov 27, 2022 · In this section, we present the scheme of Newton-MinMax and establish a global convergence rate guarantee. Moreover, we provide intuition into ...
Apr 23, 2024 · Abstract. We propose and analyze several inexact regularized Newton-type methods for finding a global saddle point of convex-concave ...
We propose and analyze exact and inexact regularized Newton-type methods for finding a global saddle point of a convex-concave unconstrained min-max ...
Oct 23, 2022 · In this paper, we examine how second-order information can be used to speed up extra-gradient methods, even under inexactness. Specifically, we ...
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We propose and analyze exact and inexact regularized Newton-type methods for finding a global saddle point of a convex-concave unconstrained min-max ...
Explicit second-order min-max optimization methods with optimal convergence guarantee ... First-order algorithms for min-max optimization in geodesic metric ...
The proposed methods are shown to generate iterates that remain within a bounded set, and the averaged iterates converge to an ε-saddle point ...