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Optimal Sparse Singular Value Decomposition for High-Dimensional High-Order Data
In this article, we consider the sparse tensor singular value decomposition, which aims for dimension reduction on high-dimensional high-order data with certain sparsity structure. A method named sparse tensor alternating thresholding for singular value decomposition (STAT-SVD) is proposed. The prop...
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| Pubblicato in: | J Am Stat Assoc |
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| Autori principali: | , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
2019
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8290930/ https://ncbi.nlm.nih.gov/pubmed/34290464 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1080/01621459.2018.1527227 |
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