| Presentation | 2014-11-17 Regularized multi-task learning for multi-dimensional log-density gradient estimation Ikko YAMANE, Hiroaki SASAKI, Masashi SUGIYAMA, |
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| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Log-density gradient estimation is a fundamental statistical problem and it has various practical applications such as clustering and a measure for non-Gaussianity. A naive two-step approach of first estimating the density and then taking its log-gradient does not perform well because an accurate density estimate does not necessarily lead to an accurate log-density gradient estimate. To cope with this problem, a method to directly estimate the log-density gradient without density estimation was explored. However, even with the direct estimator, high-dimensional log-density gradient estimation is still challenging. In this paper, we propose to apply regularized multi-task learning to direct log-density gradient estimation and show its usefulness experimentally. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Multi-task learning / log-density gradient estimation |
| Paper # | IBISML2014-58 |
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| Conference Information | |
| Committee | IBISML |
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| Conference Date | 2014/11/10(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
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| Registration To | Information-Based Induction Sciences and Machine Learning (IBISML) |
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| Language | ENG |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Regularized multi-task learning for multi-dimensional log-density gradient estimation |
| Sub Title (in English) | |
| Keyword(1) | Multi-task learning |
| Keyword(2) | log-density gradient estimation |
| 1st Author's Name | Ikko YAMANE |
| 1st Author's Affiliation | Department of Computer Science, Tokyo Institute of Technology() |
| 2nd Author's Name | Hiroaki SASAKI |
| 2nd Author's Affiliation | Department of Complexity Science and Engineering, University of Tokyo |
| 3rd Author's Name | Masashi SUGIYAMA |
| 3rd Author's Affiliation | Department of Complexity Science and Engineering, University of Tokyo |
| Date | 2014-11-17 |
| Paper # | IBISML2014-58 |
| Volume (vol) | vol.114 |
| Number (no) | 306 |
| Page | pp.pp.- |
| #Pages | 7 |
| Date of Issue | |