Robust and Discriminative Labeling for Multi-Label Active Learning Based on Maximum Correntropy Criterion
Multi-label learning draws great interests in many real world applications. It is a highly costly task to assign many labels by the oracle for one instance. Meanwhile, it is also hard to build a good model without diagnosing discriminative labels. Can we reduce the label costs and improve the abilit...
Ausführliche Beschreibung
Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 26(2017), 4 vom: 07. Apr., Seite 1694-1707
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| 1. Verfasser: |
Du, Bo
(VerfasserIn) |
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| Weitere Verfasser: |
Wang, Zengmao,
Zhang, Lefei,
Zhang, Liangpei,
Tao, Dacheng |
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| Format: | Online-Aufsatz
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| Sprache: | English |
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| Veröffentlicht: |
2017
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
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| Schlagworte: | Journal Article |
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