Multi-label metric transfer learning jointly considering instance space and label space distribution divergence
Multi-label learning deals with problems in which each instance is associated with a set of labels. Most multi-label learning algorithms ignore the potential distribution differences between the training domain and the test domain in the instance space and label space, as well as the intrinsic geome...
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Main Authors: | , , , , , , |
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其他作者: | |
格式: | Article |
語言: | English |
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2019
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主題: | |
在線閱讀: | https://hdl.handle.net/10356/86081 http://hdl.handle.net/10220/48323 |
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機構: | Nanyang Technological University |
語言: | English |