Distributed non-convex regularization for generalized linear regression

dc.contributor.authorSun, Xiaofei
dc.contributor.authorZhang, Jingyu
dc.contributor.authorLiu, Zhongmo
dc.contributor.authorPolat, Kemal
dc.contributor.authorGai, Yujie
dc.contributor.authorGao, Wenliang
dc.date.accessioned2024-09-25T19:58:35Z
dc.date.available2024-09-25T19:58:35Z
dc.date.issued2024
dc.departmentAbant İzzet Baysal Üniversitesien_US
dc.description.abstractDistributed penalized generalized linear regression algorithms have been widely studied in recent years. However, they all assume that the data should be randomly distributed. In real applications, this assumption is not necessarily true, since the whole data are often stored in a non-random manner. To tackle this issue, a non- convex penalized distributed pilot sample surrogate negative log-likelihood learning procedure is developed, which can realize distributed high-dimensional variable selection for generalized linear models, and be adaptive to the non-random situations. The established theoretical results and numerical studies all validate the proposed method.en_US
dc.identifier.doi10.1016/j.eswa.2024.124177
dc.identifier.issn0957-4174
dc.identifier.issn1873-6793
dc.identifier.scopus2-s2.0-85193248200en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.urihttps://doi.org/10.1016/j.eswa.2024.124177
dc.identifier.urihttps://hdl.handle.net/20.500.12491/13640
dc.identifier.volume252en_US
dc.identifier.wosWOS:001300455100001en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherPergamon-Elsevier Science Ltden_US
dc.relation.ispartofExpert Systems With Applicationsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmzYK_20240925en_US
dc.subjectGeneralized linear regressionen_US
dc.subjectBig dataen_US
dc.subjectVariable selectionen_US
dc.subjectRegularized learningen_US
dc.titleDistributed non-convex regularization for generalized linear regressionen_US
dc.typeArticleen_US

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