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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...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2017
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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. |
format | Online Article Text |
id | pubmed-5408075 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
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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