CP decomposition and low-rank approximation of antisymmetric tensors

Fuente: arXiv
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Main Authors: Begovic, Erna, Perisa, Lana
Format: Preprint
Published: 2022
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author Begovic, Erna
Perisa, Lana
author_facet Begovic, Erna
Perisa, Lana
contents For the antisymmetric tensors the paper examines a low-rank approximation which is represented via only three vectors. We describe a suitable low-rank format and propose an alternating least squares structure-preserving algorithm for finding such approximation. Moreover, we show that this approximation problem is equivalent to the problem of finding the best multilinear low-rank antisymmetric approximation and, consequently, equivalent to the problem of finding the best unstructured rank-$1$ approximation. The case of partial antisymmetry is also discussed. The algorithms are implemented in Julia programming language and their numerical performance is discussed.
format Preprint
id arxiv_https___arxiv_org_abs_2212_13389
institution arXiv
publishDate 2022
record_format arxiv
spellingShingle CP decomposition and low-rank approximation of antisymmetric tensors
Begovic, Erna
Perisa, Lana
Numerical Analysis
15A69
For the antisymmetric tensors the paper examines a low-rank approximation which is represented via only three vectors. We describe a suitable low-rank format and propose an alternating least squares structure-preserving algorithm for finding such approximation. Moreover, we show that this approximation problem is equivalent to the problem of finding the best multilinear low-rank antisymmetric approximation and, consequently, equivalent to the problem of finding the best unstructured rank-$1$ approximation. The case of partial antisymmetry is also discussed. The algorithms are implemented in Julia programming language and their numerical performance is discussed.
title CP decomposition and low-rank approximation of antisymmetric tensors
topic Numerical Analysis
15A69
url https://arxiv.org/abs/2212.13389