Show simple item record

dc.contributor.advisorGhosh, Joydeepen
dc.contributor.advisorMooney, Raymond J. (Raymond Joseph)en
dc.creatorAcharya, Ayanen
dc.date.accessioned2015-09-25T20:22:56Zen
dc.date.available2015-09-25T20:22:56Zen
dc.date.issued2015-08en
dc.date.submittedAugust 2015en
dc.identifierdoi:10.15781/T2HS3Sen
dc.identifier.urihttp://hdl.handle.net/2152/31414en
dc.descriptiontexten
dc.description.abstractIn several applications, scarcity of labeled data is a challenging problem that hinders the predictive capabilities of machine learning algorithms. Additionally, the distribution of the data changes over time, rendering models trained with older data less capable of discovering useful structure from the newly available data. Transfer learning is a convenient framework to overcome such problems where the learning of a model specific to a domain can benefit the learning of other models in other domains through either simultaneous training of domains or sequential transfer of knowledge from one domain to the others. This thesis explores the opportunities of knowledge transfer in the context of a few applications pertaining to object recognition from images, text analysis, network modeling and recommender systems, using probabilistic latent variable models as building blocks. Both simultaneous and sequential knowledge transfer are achieved through the latent variables, either by sharing these across multiple related domains (for simultaneous learning) or by adapting their distributions to fit data from a new domain (for sequential learning).en
dc.format.mimetypeapplication/pdfen
dc.language.isoenen
dc.subjectTransfer learningen
dc.subjectMultitask learningen
dc.subjectGamma processen
dc.subjectPoisson factorizationen
dc.subjectSupervised topic modelen
dc.titleKnowledge transfer using latent variable modelsen
dc.typeThesisen
dc.date.updated2015-09-25T20:22:56Zen
dc.contributor.committeeMemberShakkottai, Sanjayen
dc.contributor.committeeMemberSanghavi, Sujayen
dc.contributor.committeeMemberRajan, Sujuen
dc.description.departmentElectrical and Computer Engineeringen
thesis.degree.departmentElectrical and Computer Engineeringen
thesis.degree.disciplineElectrical and Computer engineeringen
thesis.degree.grantorThe University of Texas at Austinen
thesis.degree.levelDoctoralen
thesis.degree.nameDoctor of Philosophyen
dc.creator.orcid0000-0003-3023-4337en


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record