Symplectic Extra-gradient Type Method for Solving General Non-monotone Inclusion Problem

Fuente: arXiv
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Main Authors: Yuan, Ya-xiang, Zhang, Yi
Format: Preprint
Published: 2024
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author Yuan, Ya-xiang
Zhang, Yi
author_facet Yuan, Ya-xiang
Zhang, Yi
contents In recent years, accelerated extra-gradient methods have attracted much attention by researchers, for solving monotone inclusion problems. A limitation of most current accelerated extra-gradient methods lies in their direct utilization of the initial point, which can potentially decelerate numerical convergence rate. In this work, we present a new accelerated extra-gradient method, by utilizing the symplectic acceleration technique. We establish the inverse of quadratic convergence rate by employing the Lyapunov function technique. Also, we demonstrate a faster inverse of quadratic convergence rate alongside its weak convergence property under stronger assumptions. To improve practical efficiency, we introduce a line search technique for our symplectic extra-gradient method. Theoretically, we prove the convergence of the symplectic extra-gradient method with line search. Numerical tests show that this adaptation exhibits faster convergence rates in practice compared to several existing extra-gradient type methods.
format Preprint
id arxiv_https___arxiv_org_abs_2406_10793
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Symplectic Extra-gradient Type Method for Solving General Non-monotone Inclusion Problem
Yuan, Ya-xiang
Zhang, Yi
Optimization and Control
47J20, 47H05, 65K10, 65K15, 65Y20, 90C30, 90C52
In recent years, accelerated extra-gradient methods have attracted much attention by researchers, for solving monotone inclusion problems. A limitation of most current accelerated extra-gradient methods lies in their direct utilization of the initial point, which can potentially decelerate numerical convergence rate. In this work, we present a new accelerated extra-gradient method, by utilizing the symplectic acceleration technique. We establish the inverse of quadratic convergence rate by employing the Lyapunov function technique. Also, we demonstrate a faster inverse of quadratic convergence rate alongside its weak convergence property under stronger assumptions. To improve practical efficiency, we introduce a line search technique for our symplectic extra-gradient method. Theoretically, we prove the convergence of the symplectic extra-gradient method with line search. Numerical tests show that this adaptation exhibits faster convergence rates in practice compared to several existing extra-gradient type methods.
title Symplectic Extra-gradient Type Method for Solving General Non-monotone Inclusion Problem
topic Optimization and Control
47J20, 47H05, 65K10, 65K15, 65Y20, 90C30, 90C52
url https://arxiv.org/abs/2406.10793