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Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/135791
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dc.contributor.authorPapa, João Paulo-
dc.contributor.authorRosa, Gustavo Henrique de-
dc.contributor.authorMarana, Aparecido Nilceu-
dc.contributor.authorScheirer, Walter-
dc.contributor.authorCox, David Daniel-
dc.date.accessioned2016-03-02T13:04:27Z-
dc.date.accessioned2016-10-25T21:33:29Z-
dc.date.available2016-03-02T13:04:27Z-
dc.date.available2016-10-25T21:33:29Z-
dc.date.issued2015-
dc.identifierhttp://dx.doi.org/10.1016/j.jocs.2015.04.014-
dc.identifier.citationJournal of Computational Science, v. 1, p. 1, 2015.-
dc.identifier.issn1877-7503-
dc.identifier.urihttp://hdl.handle.net/11449/135791-
dc.identifier.urihttp://acervodigital.unesp.br/handle/11449/135791-
dc.description.abstractDiscriminative learning of Restricted Boltzmann Machines has been recently introduced as an alternative to provide a self-contained approach for both unsupervised feature learning and classification purposes. However, one of the main problems faced by researchers interested in such approach concerns with a proper selection of its parameters, which play an important role in its final performance. In this paper, we introduced some meta-heuristic techniques for this purpose, as well as we showed they can be more accurate than a random search, which is commonly used technique in several works.en
dc.description.sponsorshipConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)-
dc.description.sponsorshipFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)-
dc.format.extent14-18-
dc.language.isoeng-
dc.sourceCurrículo Lattes-
dc.subjectDiscriminative restricted boltzmann machinesen
dc.subjectModel selectionen
dc.subjectDeep learningen
dc.titleModel selection for discriminative restricted boltzmann machines through meta-heuristic techniquesen
dc.typeoutro-
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)-
dc.contributor.institutionHarvard University-
dc.description.affiliationUniversidade Estadual Paulista Júlio de Mesquita Filho, Departamento de Computação, Faculdade de Ciências de Bauru, Bauru, Av. Engenheiro Luiz Edmundo Carrijo Coube, 14-01, Vargem Limpa, CEP 17033-360, SP, Brasil-
dc.description.affiliationHarvard University, Cambridge, MA, USA-
dc.description.affiliationUnespUniversidade Estadual Paulista Júlio de Mesquita Filho, Departamento de Computação, Faculdade de Ciências de Bauru, Bauru, Av. Engenheiro Luiz Edmundo Carrijo Coube, 14-01, Vargem Limpa, CEP 17033-360, SP, Brasil-
dc.description.sponsorshipIdFAPESP: 2013/20387-7-
dc.description.sponsorshipIdFAPESP: 2014/16250-9-
dc.description.sponsorshipIdCNPq: 303182/2011-3-
dc.description.sponsorshipIdCNPq: 470571/2013-6-
dc.identifier.doi10.1016/j.jocs.2015.04.014-
dc.rights.accessRightsAcesso restrito-
dc.relation.ispartofJournal of Computational Science-
dc.identifier.lattes6027713750942689-
dc.identifier.lattes9039182932747194-
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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