Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/138954
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dc.contributor.authorWei, Pengfeien_US
dc.contributor.authorKe, Yipingen_US
dc.contributor.authorGoh, Chi Keongen_US
dc.date.accessioned2020-05-14T05:26:09Z-
dc.date.available2020-05-14T05:26:09Z-
dc.date.issued2019-
dc.identifier.citationWei, P., Ke, Y., & Goh, C. K. (2018). A general domain specific feature transfer framework for hybrid domain adaptation. IEEE Transactions on Knowledge and Data Engineering, 31(8), 1440-1451. doi:10.1109/TKDE.2018.2864732en_US
dc.identifier.issn1041-4347en_US
dc.identifier.urihttps://hdl.handle.net/10356/138954-
dc.description.abstractHeterogeneous domain adaptation needs supplementary information to link up different domains. However, such supplementary information may not always be available in real cases. In this paper, a new problem setting called hybrid domain adaptation is investigated. It is a special case of heterogeneous domain adaptation, in which different domains share some common features, but also have their own domain specific features. We leverage upon common features instead of supplementary information to achieve effective adaptation. We propose a general domain specific feature transfer framework, which can link up different domains using common features and simultaneously reduce domain divergences. Specifically, we learn the translations between common features and domain specific features. Then, we cross-use the learned translations to transfer the domain specific features of one domain to another domain. Finally, we compose a homogeneous space in which the domain divergences are minimized. We instantiate the general framework to a linear case and a nonlinear case. Extensive experiments verify the effectiveness of the two cases.en_US
dc.description.sponsorshipNRF (Natl Research Foundation, S’pore)en_US
dc.description.sponsorshipMOE (Min. of Education, S’pore)en_US
dc.language.isoenen_US
dc.relation.ispartofIEEE Transactions on Knowledge and Data Engineeringen_US
dc.rights© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: https://doi.org/10.1109/TKDE.2018.2864732.en_US
dc.subjectEngineering::Computer science and engineeringen_US
dc.titleA general domain specific feature transfer framework for hybrid domain adaptationen_US
dc.typeJournal Articleen
dc.contributor.schoolSchool of Computer Science and Engineeringen_US
dc.identifier.doi10.1109/TKDE.2018.2864732-
dc.description.versionAccepted versionen_US
dc.identifier.scopus2-s2.0-85052575719-
dc.identifier.issue8en_US
dc.identifier.volume31en_US
dc.identifier.spage1440en_US
dc.identifier.epage1451en_US
dc.subject.keywordsKnowledge Transferen_US
dc.subject.keywordsDomain Specific Featureen_US
item.grantfulltextopen-
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