Unsupervised model adaptation for multivariate calibration by domain adaptation-regularization based kernel partial least square.

Shan, Peng; Bi, Yiming; Li, Zhigang; Wang, Qiaoyun; He, Zhonghai; Zhao, Yuhui; Peng, Silong

Shan, Peng; Bi, Yiming; Li, Zhigang; Wang, Qiaoyun; He, Zhonghai; Zhao, Yuhui; Peng, Silong.

Afiliação

Shan P; College of Information Science and Engineering, Northeastern University, Shenyang 110819, Liaoning Province, China. Electronic address: peng.shan@neuq.edu.cn.
Bi Y; Technology Center, China Tobacco Zhejiang Industrial Co., Ltd, Hangzhou 310008, Zhejiang Province, China.
Li Z; College of Information Science and Engineering, Northeastern University, Shenyang 110819, Liaoning Province, China.
Wang Q; College of Information Science and Engineering, Northeastern University, Shenyang 110819, Liaoning Province, China.
He Z; College of Information Science and Engineering, Northeastern University, Shenyang 110819, Liaoning Province, China.
Zhao Y; School Of Computer Science and Engineering, Northeastern University, Shenyang 110819, Liaoning Province, China.
Peng S; Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.

Spectrochim Acta A Mol Biomol Spectrosc ; 292: 122418, 2023 May 05.

Article em En | MEDLINE | ID: mdl-36736045

Palavras-chave

Domain-invariant feature representation; Kernel partial least squares; Model adaptation; Projected maximum mean discrepancy

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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Spectrochim Acta A Mol Biomol Spectrosc Assunto da revista: BIOLOGIA MOLECULAR Ano de publicação: 2023 Tipo de documento: Article

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