Perturbations of the Tcur Decomposition for Tensor Valued Data in the Tucker Format

被引:0
作者
Maolin Che
Juefei Chen
Yimin Wei
机构
[1] Southwestern University of Finance and Economics,School of Mathematics
[2] Hong Kong Science Park,The Center for Intelligent Multidimensional Data Analysis
[3] Fudan University,School of Mathematical Sciences
[4] Fudan University,School of Mathematical Sciences and Key Laboratory of Mathematics for Nonlinear Sciences
来源
Journal of Optimization Theory and Applications | 2022年 / 194卷
关键词
Tensor CUR decomposition; Low multilinear rank approximation; Maximal volume sub-matrices; Mode-; unfolding; Tucker decomposition; 15A18; 65F10; 65F15;
D O I
暂无
中图分类号
学科分类号
摘要
The tensor CUR decomposition in the Tucker format is a special case of Tucker decomposition with a low multilinear rank, where factor matrices are obtained by selecting some columns from the mode-n unfolding of the tensor. We perform a thorough investigation of what happens to the approximations in the presence of noise. We present two forms of the tensor CUR decomposition and deduce the errors of the approximation. We illustrate how the choice of columns from each mode-n unfolding reflects the quality of the tensor CUR approximation via some numerical examples.
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页码:852 / 877
页数:25
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