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

• المؤلفون الرئيسيون: Jiang, Siyu, Xu, Yonghui, Wang, Tengyun, Yang, Haizhi, Qiu, Shaojian, Yu, Han, Song, Hengjie
• مؤلفون آخرون: School of Computer Science and Engineering
• التنسيق: مقال
• اللغة: English
• منشور في: 2019
• الموضوعات: Transfer Learning; Metric Learning; DRNTU::Engineering::Computer science and engineering
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/86081; http://hdl.handle.net/10220/48323

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...