n-Mode Singular Vector Selection in Higher-Order Singular Value Decomposition

被引：1
|
作者：
Inoue, Kohei [1 ]
Urahama, Kiichi [1 ]
机构：
[1] Kyushu Univ, Fac Design, Fukuoka 8158540, Japan
来源：
IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES | 2008年 / E91A卷 / 11期
关键词：
dimensionality reduction; higher-order singular value decomposition; n-mode singular vector;
D O I：
10.1093/ietfec/e91-a.11.3380
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
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.
引用
收藏
页码：3380 / 3384
页数：5
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