| Presentation | 2013-07-12 Variational Bayes in Directional Statistics Toshihisa TANAKA, Masayuki KOBAYASHI, |
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| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Estimation of the parameters of distribution with observed data is crucial in signal processing and machine learning. A well-known estimation method is Bayesian estimation, which is useful for restraining overfitting and less affected by outliers compared to classical maximum likelihood estimation. This article derives an estimator of the parameters in a von Mises mixture model, which is an important distribution in directional statistics. More specifically, we focus on the fact that the von Mises distribution is derived from the bivariate Gaussian distribution. Based on this, a variational Bayesian method for a mixture Gaussian model is applied to estimating the parameters of the mixture von Mises model. Experimental results support the analysis. |
| Keyword(in Japanese) | (See Japanese page) |
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| Paper # | CAS2013-21,VLD2013-31,SIP2013-51,MSS2013-21 |
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| Committee | VLD |
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| Conference Date | 2013/7/4(1days) |
| Place (in Japanese) | (See Japanese page) |
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| Registration To | VLSI Design Technologies (VLD) |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Variational Bayes in Directional Statistics |
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| 1st Author's Name | Toshihisa TANAKA |
| 1st Author's Affiliation | Department of Electrical and Electronic Engineering Tokyo University of Agriculture and Technology() |
| 2nd Author's Name | Masayuki KOBAYASHI |
| 2nd Author's Affiliation | Department of Electrical and Electronic Engineering Tokyo University of Agriculture and Technology |
| Date | 2013-07-12 |
| Paper # | CAS2013-21,VLD2013-31,SIP2013-51,MSS2013-21 |
| Volume (vol) | vol.113 |
| Number (no) | 119 |
| Page | pp.pp.- |
| #Pages | 6 |
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