Class-rebalanced wasserstein distance for multi-source domain adaptation

In the study of machine learning, multi-source domain adaptation (MSDA) handles multiple datasets which are collected from different distributions by using domain-invariant knowledge extraction. However, the current studies mainly employ features and raw labels on the joint space to perform domain a...

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Veröffentlicht in:	Applied intelligence (Dordrecht, Netherlands) Netherlands), 2023-04, Vol.53 (7), p.8024-8038
Hauptverfasser:	Wang, Qi, Wang, Shengsheng, Wang, Bilin
Format:	Artikel
Sprache:	eng
Schlagworte:	Adaptation Artificial Intelligence Computer Science Data correlation Datasets Domains Feature extraction Generators Knowledge Machine learning Machines Manufacturing Mechanical Engineering Processes Transportation planning
Online-Zugang:	Volltext
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