Stochastic density ratio estimation and its application to feature selection

dc.creatorBraga, Ígor Assis
dc.creatorMonard, Maria Carolina
dc.creatorVapnik, Vladimir
dc.date.accessioned2016-03-04T18:31:34Z
dc.date.accessioned2018-07-04T17:07:40Z
dc.date.available2016-03-04T18:31:34Z
dc.date.available2018-07-04T17:07:40Z
dc.date.created2016-03-04T18:31:34Z
dc.date.issued2015-07
dc.identifierInternational Joint Conference on Artificial Intelligence, 24th, 2015, Buenos Aires.
dc.identifier9781577357384
dc.identifierhttp://www.producao.usp.br/handle/BDPI/49796
dc.identifierhttp://www.ijcai.org/Proceedings/15/Papers/620.pdf
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1645020
dc.description.abstractIn this work, we deal with a relatively new statistical tool in machine learning: the estimation of the ratio of two probability densities, or density ratio estimation for short. As a side piece of research that gained its own traction, we also tackle the task of parameter selection in learning algorithms based on kernel methods.
dc.languageeng
dc.publisherAssociation for the Advancement of Artificial Intelligence - AAAI
dc.publisherInternational Joint Conferences on Artificial Intelligence - IJCAI
dc.publisherSociedad Argentina de Informática e Investigación Operativa - SADIO
dc.publisherUniversidad de Buenos Aires - UBA
dc.publisherUniversidad Nacional del Sur - UNS
dc.publisherMinisterio de Ciencia, Tecnología e Innovación Productiva
dc.publisherConsejo Nacional de Investigaciones Científicas y Técnicas – CONICET
dc.publisherBuenos Aires
dc.relationInternational Joint Conference on Artificial Intelligence, 24th
dc.rightsrestrictedAccess
dc.titleStochastic density ratio estimation and its application to feature selection
dc.typeActas de congresos


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