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dc.contributor.advisorBengio, Yoshuafr
dc.contributor.authorLarochelle, Hugofr
dc.date.accessioned2012-03-07T01:20:25Z
dc.date.available2012-03-07T01:20:25Z
dc.date.issued2009-04-16fr
dc.date.submitted2008fr
dc.identifier.urihttp://hdl.handle.net/1866/6435
dc.subjectApprentissage non-superviséfr
dc.subjectRéseau de neurones artificielfr
dc.subjectMachine de Boltzmann restreintefr
dc.subjectAutoassociateurfr
dc.subjectAutoencodeurfr
dc.subjectArchitecture profondefr
dc.subjectUnsupervised learningfr
dc.subjectNeural networkfr
dc.subjectRestricted Boltzmann machinefr
dc.subjectAutoassociatorfr
dc.subjectAutoencoderfr
dc.subjectDeep architecturefr
dc.subjectDeep learningfr
dc.titleÉtude de techniques d'apprentissage non-supervisé pour l'amélioration de l'entraînement supervisé de modèles connexionnistesfr
dc.typeThèse ou mémoire / Thesis or Dissertationfr
etd.degree.disciplineInformatiquefr
etd.degree.grantorUniversité de Montréalfr
etd.degree.levelDoctorat / Doctoralfr
etd.degree.namePh. D.fr
dcterms.descriptionThèse numérisée par la Division de la gestion de documents et des archives de l'Université de Montréal.fr
dcterms.languagefrafr


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