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Items where Author is "Yang, Zaoli"

Items where Author is "Yang, Zaoli"

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disagreement cotraining feature argument and select algorithm L1 penalized logistics regression algorithm noise learning theory semisupervised classification
Number of items: 5.

disagreement cotraining

Yang, Zaoli, Zhang, Weijian, Han, Chunjia, Li, Yuchen, Yang, Mu and Ieromonachou, Petros ORCID logoORCID: https://orcid.org/0000-0002-5842-9585 (2022) A semisupervised classification algorithm combining noise learning theory and a disagreement cotraining framework. Information Sciences, 622. pp. 889-902. ISSN 0020-0255 (doi:10.1016/j.ins.2022.11.115)

feature argument and select algorithm

Yang, Zaoli, Zhang, Weijian, Han, Chunjia, Li, Yuchen, Yang, Mu and Ieromonachou, Petros ORCID logoORCID: https://orcid.org/0000-0002-5842-9585 (2022) A semisupervised classification algorithm combining noise learning theory and a disagreement cotraining framework. Information Sciences, 622. pp. 889-902. ISSN 0020-0255 (doi:10.1016/j.ins.2022.11.115)

L1 penalized logistics regression algorithm

Yang, Zaoli, Zhang, Weijian, Han, Chunjia, Li, Yuchen, Yang, Mu and Ieromonachou, Petros ORCID logoORCID: https://orcid.org/0000-0002-5842-9585 (2022) A semisupervised classification algorithm combining noise learning theory and a disagreement cotraining framework. Information Sciences, 622. pp. 889-902. ISSN 0020-0255 (doi:10.1016/j.ins.2022.11.115)

noise learning theory

Yang, Zaoli, Zhang, Weijian, Han, Chunjia, Li, Yuchen, Yang, Mu and Ieromonachou, Petros ORCID logoORCID: https://orcid.org/0000-0002-5842-9585 (2022) A semisupervised classification algorithm combining noise learning theory and a disagreement cotraining framework. Information Sciences, 622. pp. 889-902. ISSN 0020-0255 (doi:10.1016/j.ins.2022.11.115)

semisupervised classification

Yang, Zaoli, Zhang, Weijian, Han, Chunjia, Li, Yuchen, Yang, Mu and Ieromonachou, Petros ORCID logoORCID: https://orcid.org/0000-0002-5842-9585 (2022) A semisupervised classification algorithm combining noise learning theory and a disagreement cotraining framework. Information Sciences, 622. pp. 889-902. ISSN 0020-0255 (doi:10.1016/j.ins.2022.11.115)

This list was generated on Sun Dec 22 11:41:25 2024 UTC.