Dimensionality reduction algorithm of tensor data based on orthogonal tucker decomposition and local discrimination difference

Dimensionality Reduction (DR) is a significant subject which have aroused extensive attention of researchers. In this paper, a novel method is proposed to reduce the dimensionality of tensor data based on orthogonal Tucker decomposition model and local discrimination difference regularization (OTDLD...

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Veröffentlicht in:	Applied intelligence (Dordrecht, Netherlands) Netherlands), 2022-09, Vol.52 (12), p.14518-14540
Hauptverfasser:	Gao, Wenxu, Ma, Zhengming, Yuan, Xuejing
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Artificial Intelligence Clustering Computer Science Constraint modelling Decomposition Machines Manufacturing Mathematical analysis Mechanical Engineering Processes Reduction Regularization Tensors
Online-Zugang:	Volltext
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