N-mode singular vector selection in higher-order singular value decomposition

Kohei Inoue, Kiichi Urahama

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)3380-3384
Number of pages5
JournalIEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
VolumeE91-A
Issue number11
DOIs
Publication statusPublished - Nov 2008

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Singular Vectors
Singular value decomposition
Higher Order
Tensors
Tensor
Low-rank Approximation
Square Functions
Simultaneous Approximation
Cost functions
Cost Function
Least Squares
Upper bound
Experimental Results

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering
  • Computer Graphics and Computer-Aided Design
  • Applied Mathematics
  • Signal Processing

Cite this

N-mode singular vector selection in higher-order singular value decomposition. / Inoue, Kohei; Urahama, Kiichi.

In: IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, Vol. E91-A, No. 11, 11.2008, p. 3380-3384.

Research output: Contribution to journalArticle

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