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A modified subgradient extragradient method for solving monotone variational inequalities

In the setting of Hilbert space, a modified subgradient extragradient method is proposed for solving Lipschitz-continuous and monotone variational inequalities defined on a level set of a convex function. Our iterative process is relaxed and self-adaptive, that is, in each iteration, calculating two...

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Detalles Bibliográficos
Autores principales: He, Songnian, Wu, Tao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5408075/
https://www.ncbi.nlm.nih.gov/pubmed/28515617
http://dx.doi.org/10.1186/s13660-017-1366-3
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author He, Songnian
Wu, Tao
author_facet He, Songnian
Wu, Tao
author_sort He, Songnian
collection PubMed
description In the setting of Hilbert space, a modified subgradient extragradient method is proposed for solving Lipschitz-continuous and monotone variational inequalities defined on a level set of a convex function. Our iterative process is relaxed and self-adaptive, that is, in each iteration, calculating two metric projections onto some half-spaces containing the domain is involved only and the step size can be selected in some adaptive ways. A weak convergence theorem for our algorithm is proved. We also prove that our method has [Formula: see text] convergence rate.
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spelling pubmed-54080752017-05-15 A modified subgradient extragradient method for solving monotone variational inequalities He, Songnian Wu, Tao J Inequal Appl Research In the setting of Hilbert space, a modified subgradient extragradient method is proposed for solving Lipschitz-continuous and monotone variational inequalities defined on a level set of a convex function. Our iterative process is relaxed and self-adaptive, that is, in each iteration, calculating two metric projections onto some half-spaces containing the domain is involved only and the step size can be selected in some adaptive ways. A weak convergence theorem for our algorithm is proved. We also prove that our method has [Formula: see text] convergence rate. Springer International Publishing 2017-04-27 2017 /pmc/articles/PMC5408075/ /pubmed/28515617 http://dx.doi.org/10.1186/s13660-017-1366-3 Text en © The Author(s) 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Research
He, Songnian
Wu, Tao
A modified subgradient extragradient method for solving monotone variational inequalities
title A modified subgradient extragradient method for solving monotone variational inequalities
title_full A modified subgradient extragradient method for solving monotone variational inequalities
title_fullStr A modified subgradient extragradient method for solving monotone variational inequalities
title_full_unstemmed A modified subgradient extragradient method for solving monotone variational inequalities
title_short A modified subgradient extragradient method for solving monotone variational inequalities
title_sort modified subgradient extragradient method for solving monotone variational inequalities
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5408075/
https://www.ncbi.nlm.nih.gov/pubmed/28515617
http://dx.doi.org/10.1186/s13660-017-1366-3
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