Randomized algorithms for the computation of multilinear rank-(μ1,μ2,μ3) approximations

We present some randomized algorithms for computing multilinear rank- ( μ 1 , μ 2 , μ 3 ) approximations of tensors by combining the sparse subspace embedding and the singular value decomposition. The error bound for this algorithm with the high probability is obtained by the properties of sparse su...

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Bibliographic Details
Published in:	Journal of global optimization Vol. 87; no. 2-4; pp. 373 - 403
Main Authors:	Che, Maolin, Wei, Yimin, Xu, Yanwei
Format:	Journal Article
Language:	English
Published:	New York Springer US 01.11.2023 Springer
Subjects:	Algorithms Analysis Computer Science Mathematics Mathematics and Statistics Operations Research/Decision Theory Optimization Real Functions approximation Multilinear rank 65F10 Singular values Randomized algorithms Sparse subspace embedding 65F15 Random projection The power scheme Singular value decomposition 15A18
ISSN:	0925-5001, 1573-2916
Online Access:	Get full text
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