Convergence analysis of an SVD-based algorithm for the best rank-1 tensor approximation
type: Item
instance of: scholarly article
title: Convergence analysis of an SVD-based algorithm for the best rank-1 tensor approximation
zbMATH Open document ID: 1397.65055
author: Yu Guan
author: Moody T. Chu
author: Delin Chu
published in: Linear Algebra and its Applications
publication date: 2018-08-08T00:00:00Z
Mathematics Subject Classification ID: 65F15
Mathematics Subject Classification ID: 15A69
Mathematics Subject Classification ID: 15A15
Mathematics Subject Classification ID: 15A09
Mathematics Subject Classification ID: 15A23
zbMATH DE Number: 6914715
zbMATH Keywords: best rank-1 tensor approximation
zbMATH Keywords: singular value decomposition
describes a project that uses: Algorithm 862
describes a project that uses: GQTPAR
MaRDI profile type: Publication
full work available at URL: j.laa.2018.06.006
OpenAlex ID: W2806658157
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cites work: On the Global Convergence of the Alternating Least Squares Method for Rank-One Approximation to Generic Tensors
cites work: Differential equations for the analytic singular value decomposition of a matrix
cites work: Rank-one approximation to high order tensors
Wikidata QID: Q129729811
DOI: 10.1016/J.LAA.2018.06.006
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description: scientific article; zbMATH DE number 6914715