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Cited 4 time in webofscience Cited 13 time in scopus
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Revisiting subgradient extragradient methods for solving variational inequalities

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dc.contributor.authorTan, Bing-
dc.contributor.authorQin, Xiaolong-
dc.contributor.authorCho, Sun Young-
dc.date.accessioned2022-12-26T05:41:31Z-
dc.date.available2022-12-26T05:41:31Z-
dc.date.created2022-12-12-
dc.date.issued2022-08-
dc.identifier.issn1017-1398-
dc.identifier.urihttps://scholarworks.bwise.kr/gnu/handle/sw.gnu/993-
dc.description.abstractIn this paper, several extragradient algorithms with inertial effects and adaptive non-monotonic step sizes are proposed to solve pseudomonotone variational inequalities in real Hilbert spaces. The strong convergence of the proposed methods is established without the prior knowledge of the Lipschitz constant of the mapping. Some numerical experiments are given to illustrate the advantages and efficiency of the proposed schemes over previously known ones.-
dc.language영어-
dc.language.isoen-
dc.publisherSPRINGER-
dc.subjectSTRONG-CONVERGENCE-
dc.subjectPROJECTION METHODS-
dc.titleRevisiting subgradient extragradient methods for solving variational inequalities-
dc.typeArticle-
dc.contributor.affiliatedAuthorCho, Sun Young-
dc.identifier.doi10.1007/s11075-021-01243-1-
dc.identifier.scopusid2-s2.0-85123300065-
dc.identifier.wosid000745416300001-
dc.identifier.bibliographicCitationNUMERICAL ALGORITHMS, v.90, no.4, pp.1593 - 1615-
dc.relation.isPartOfNUMERICAL ALGORITHMS-
dc.citation.titleNUMERICAL ALGORITHMS-
dc.citation.volume90-
dc.citation.number4-
dc.citation.startPage1593-
dc.citation.endPage1615-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaMathematics-
dc.relation.journalWebOfScienceCategoryMathematics, Applied-
dc.subject.keywordPlusSTRONG-CONVERGENCE-
dc.subject.keywordPlusPROJECTION METHODS-
dc.subject.keywordAuthorVariational inequality-
dc.subject.keywordAuthorInertial extragradient method-
dc.subject.keywordAuthorArmjio stepsize-
dc.subject.keywordAuthorPseudomonotone mapping-
dc.subject.keywordAuthorNon-Lipschitz operator-
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