| Presentation | 2006-10-20 Simultaneous Low Rank Approximation of Tensors Kohei INOUE, Kiichi URAHAMA, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | In this paper, we propose iterative and non-iterative algorithms for simultaneous low rank approximation of tensors (SLRAT). We formulate the SLRAT as a minimization problem, in which we want to minimize the reconstruction error of tensors. We illustrate the utility of the SLRAT on image compression using hyperspectral images. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | tensor / simultaneous low rank approximation / dimensionality reduction / higher-order singular value decomposition |
| Paper # | PRMU2006-112 |
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| Conference Information | |
| Committee | PRMU |
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| Conference Date | 2006/10/13(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
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| Paper Information | |
| Registration To | Pattern Recognition and Media Understanding (PRMU) |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Simultaneous Low Rank Approximation of Tensors |
| Sub Title (in English) | |
| Keyword(1) | tensor |
| Keyword(2) | simultaneous low rank approximation |
| Keyword(3) | dimensionality reduction |
| Keyword(4) | higher-order singular value decomposition |
| 1st Author's Name | Kohei INOUE |
| 1st Author's Affiliation | Department of Visual Communication Design, Kyushu University() |
| 2nd Author's Name | Kiichi URAHAMA |
| 2nd Author's Affiliation | Department of Visual Communication Design, Kyushu University |
| Date | 2006-10-20 |
| Paper # | PRMU2006-112 |
| Volume (vol) | vol.106 |
| Number (no) | 301 |
| Page | pp.pp.- |
| #Pages | 6 |
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