数学
笛卡尔张量
张量积
张量(固有定义)
维数之咒
矩阵乘法
张量收缩
矩阵分解
计算
摄动(天文学)
张量密度
纯数学
数学分析
张量场
算法
广义相对论的精确解
特征向量
物理
量子力学
统计
量子
作者
Juefei Chen,Yimin Wei,Yanwei Xu
标识
DOI:10.1080/01630563.2022.2056198
摘要
In order to process the large-scale data, a useful tool in dimensionality reduction of a matrix, the CUR decomposition has been developed, which can compress the huge matrix with its original elements. Tensor-tensor decompositions have become prevalent and a new multiplication of a tensor based on the T-product has been presented for the tensor computation. Using the T-product, we propose a dimensionality reduction tool of three-order tensor called the T-product CUR decomposition (t-CUR decomposition for short) and analyze its stability of the perturbation. The t-CUR decomposition can reduce the size of a large-scale tensor with its original entries, its perturbation error bound is refined in the first order of the noise tensor under the spectrum norm. Numerical tests are provided to verify the results of our theoretical error analysis as well.
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