| Presentation | 2015-03-19 Semi-Supervised Low-rank GMM Learning for Multimodal Distribution Eita AOKI, Tetsuya MATSUMOTO, Noboru OHNIHSHI, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | In this study, we examine the learning method of each category distribution under underdetermined environment that category information of few data are known. Because we use multimodal data distribution, learning for each category distribution is difficult. Therefore, by using the given category information, and projecting the data into low-dimensional subspace suitable for category classification, we propose a method to GMM approximation. Specifically, we consider each category distribution as a linear combination of subclasses of the multidimensional normal distribution, and determine the projection space by appropriate criteria. In the experiment, we compared the proposed method with the conventional method by changing the parameters. In some cases, the proposed method showed higher accuracy than the conventional method. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Semi-Supervised Learning / Dimensionality Reduction / Multi-Modality |
| Paper # | BioX2014-60,PRMU2014-180 |
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| Conference Information | |
| Committee | PRMU |
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| Conference Date | 2015/3/12(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
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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) | Semi-Supervised Low-rank GMM Learning for Multimodal Distribution |
| Sub Title (in English) | |
| Keyword(1) | Semi-Supervised Learning |
| Keyword(2) | Dimensionality Reduction |
| Keyword(3) | Multi-Modality |
| 1st Author's Name | Eita AOKI |
| 1st Author's Affiliation | Graduate School of Information Science, Nagoya University() |
| 2nd Author's Name | Tetsuya MATSUMOTO |
| 2nd Author's Affiliation | Graduate School of Information Science, Nagoya University |
| 3rd Author's Name | Noboru OHNIHSHI |
| 3rd Author's Affiliation | Graduate School of Information Science, Nagoya University |
| Date | 2015-03-19 |
| Paper # | BioX2014-60,PRMU2014-180 |
| Volume (vol) | vol.114 |
| Number (no) | 521 |
| Page | pp.pp.- |
| #Pages | 6 |
| Date of Issue | |