期刊
IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES
卷 E91A, 期 11, 页码 3380-3384出版社
IEICE-INST ELECTRONICS INFORMATION COMMUNICATIONS ENG
DOI: 10.1093/ietfec/e91-a.11.3380
关键词
dimensionality reduction; higher-order singular value decomposition; n-mode singular vector
In this paper, we propose a method for selecting n-mode singular vectors in higher-order singular value decomposition. We select the minimum number of n-mode singular vectors, when the upper bound of a least-squares cost function is thresholded. The reduced n-ranks of all modes of a given tensor are determined automatically and the tensor is represented with the minimum number of dimensions. We apply the selection method to simultaneous low rank approximation of matrices. Experimental results show the effectiveness of the n-mode singular vector selection method.
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