Incomplete Multi-View Learning Under Label Shift-Reference-Cited by-同舟云学术

Incomplete Multi-View Learning Under Label Shift

Author:

Fan Ruidong¹,Ouyang Xiao¹,Luo Tingjin¹^ORCID,Hu Dewen²^ORCID,Hou Chenping¹^ORCID

Affiliation:

1. College of Science, National University of Defense Technology, Changsha, China

2. College of Intelligence Science and Technology, National University of Defense Technology, Changsha, China

Funder

NSF of China

NSF for Distinguished Young Scholars of Hunan Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Graphics and Computer-Aided Design,Software

Link

Reference47 articles.

1. Optimal transport for multi-source domain adaptation under target shift;redko;Proc Int Conf Artif Intell Statist,2019

2. Coping with label shift via distributionally robust optimisation;zhang;Proc ICLR,2021

3. LAMDA: Label matching deep domain adaptation;le;Proc ICML,2021

4. On target shift in adversarial domain adaptation;li;Proc AISTATS,2019

5. Multiple incomplete views clustering via weighted nonnegative matrix factorization with L2,1 regularization;shao;Proc PKDD,2015

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