A strongly convergent inertial inexact proximal-point algorithm for monotone inclusions with applications to variational inequalities

Autor:	Alves, M. Marques, Caballero, J. E. Navarro, Marcavillaca, R. T.
Rok vydání:	2024
Předmět:	Mathematics - Optimization and Control
Druh dokumentu:	Working Paper
Popis:	We propose an inertial variant of the strongly convergent inexact proximal-point (PP) method of Solodov and Svaiter (2000) for monotone inclusions. We prove strong convergence of our main algorithm under less restrictive assumptions on the inertial parameters when compared to previous analysis of inertial PP-type algorithms, which makes our method of interest even in finite-dimensional settings. We also performed an iteration-complexity analysis and applied our main algorithm to variational inequalities for monotone operators, obtaining strongly convergent (inertial) variants of Korpolevich's extragradient, forward-backward and Tseng's modified forward-backward methods.
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2407.03485 Zobrazit plný text záznamu View this record from Arxiv