A sequential multilinear Nyström algorithm for streaming low-rank approximation of tensors in Tucker format

Fuente: arXiv
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Main Authors: Bucci, Alberto, Hashemi, Behnam
Format: Preprint
Published: 2024
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author Bucci, Alberto
Hashemi, Behnam
author_facet Bucci, Alberto
Hashemi, Behnam
contents We present a sequential version of the multilinear Nyström algorithm which is suitable for the low-rank Tucker approximation of tensors given in a streaming format. Accessing the tensor $\mathcal{A}$ exclusively through random sketches of the original data, the algorithm effectively leverages structures in $\mathcal{A}$, such as low-rankness, and linear combinations. We present a deterministic analysis of the algorithm and demonstrate its superior speed and efficiency in numerical experiments including an application in video processing.
format Preprint
id arxiv_https___arxiv_org_abs_2407_03849
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle A sequential multilinear Nyström algorithm for streaming low-rank approximation of tensors in Tucker format
Bucci, Alberto
Hashemi, Behnam
Numerical Analysis
15A69, 65F55, 68W20
We present a sequential version of the multilinear Nyström algorithm which is suitable for the low-rank Tucker approximation of tensors given in a streaming format. Accessing the tensor $\mathcal{A}$ exclusively through random sketches of the original data, the algorithm effectively leverages structures in $\mathcal{A}$, such as low-rankness, and linear combinations. We present a deterministic analysis of the algorithm and demonstrate its superior speed and efficiency in numerical experiments including an application in video processing.
title A sequential multilinear Nyström algorithm for streaming low-rank approximation of tensors in Tucker format
topic Numerical Analysis
15A69, 65F55, 68W20
url https://arxiv.org/abs/2407.03849