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
其他作者: School of Computer Science and Engineering
格式: Article
語言:English
出版: 2019
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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