Multi-label metric transfer learning jointly considering instance space and label space distribution divergence

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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Bibliographic Details
Main Authors: Jiang, Siyu, Xu, Yonghui, Wang, Tengyun, Yang, Haizhi, Qiu, Shaojian, Yu, Han, Song, Hengjie
Other Authors: School of Computer Science and Engineering
Format: Journal Article
Language:English
Published: 2019
Subjects:
Transfer Learning
Metric Learning
DRNTU::Engineering::Computer science and engineering
Online Access:https://hdl.handle.net/10356/86081
http://hdl.handle.net/10220/48323

Internet

https://hdl.handle.net/10356/86081
http://hdl.handle.net/10220/48323

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