Towards Uncovering the Intrinsic Data Structures for Unsupervised Domain Adaptation Using Structurally Regularized Deep Clustering
Unsupervised domain adaptation (UDA) is to learn classification models that make predictions for unlabeled data on a target domain, given labeled data on a source domain whose distribution diverges from the target one. Mainstream UDA methods strive to learn domain-aligned features such that classifi...
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Détails bibliographiques
| Publié dans: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 44(2022), 10 vom: 09. Okt., Seite 6517-6533
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| Auteur principal: |
Tang, Hui
(Auteur) |
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| Autres auteurs: |
Zhu, Xiatian,
Chen, Ke,
Jia, Kui,
Chen, C L Philip |
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| Format: | Article en ligne
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| Langue: | English |
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| Publié: |
2022
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| Accès à la collection: | IEEE transactions on pattern analysis and machine intelligence
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| Sujets: | Journal Article
Research Support, Non-U.S. Gov't |
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