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: | Jiang, Siyu, Xu, Yonghui, Wang, Tengyun, Yang, Haizhi, Qiu, Shaojian, Yu, Han, Song, Hengjie |
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Other Authors: | School of Computer Science and Engineering |
Format: | Article |
Language: | English |
Published: |
2019
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Subjects: | |
Online Access: | https://hdl.handle.net/10356/86081 http://hdl.handle.net/10220/48323 |
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Institution: | Nanyang Technological University |
Language: | English |
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