A sequential multilinear Nyström algorithm for streaming low-rank approximation of tensors in Tucker format
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arXiv
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866916363712331776 |
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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 |
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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 |