| Presentation | 1998/3/20 EM Algorithm with Split and Merge Operations and its application to Mixture Density Estimation Naonori UEDA, Ryohei NAKANO, |
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| PDF Download Page | PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | The EM algorithm has been been extensively used for a wide variety of parameter estimation problems with hidden or latent variables to compute the maximum likelihood estimates. The algorithm, however, suffers from the local maxima problem in practice. In this report, focusing on the case of discrete hidden variables, we present a split and merge EM algorithm to overcome the local maxima problem. We apply the proposed algorithm to Gaussian mixture density estimation problem and show that the algorithm could impressively improve likelihood values. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | EM algorithm / Maximum likelihood estimation / Gaussian mixture estimation problem / Split& Merge operations |
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| Conference Information | |
| Committee | NC |
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| Conference Date | 1998/3/20(1days) |
| Place (in Japanese) | (See Japanese page) |
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| Topics (in Japanese) | (See Japanese page) |
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| Registration To | Neurocomputing (NC) |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | EM Algorithm with Split and Merge Operations and its application to Mixture Density Estimation |
| Sub Title (in English) | |
| Keyword(1) | EM algorithm |
| Keyword(2) | Maximum likelihood estimation |
| Keyword(3) | Gaussian mixture estimation problem |
| Keyword(4) | Split& Merge operations |
| 1st Author's Name | Naonori UEDA |
| 1st Author's Affiliation | NTT Communication Science Laboratories() |
| 2nd Author's Name | Ryohei NAKANO |
| 2nd Author's Affiliation | NTT Communication Science Laboratories |
| Date | 1998/3/20 |
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| Volume (vol) | vol.97 |
| Number (no) | 624 |
| Page | pp.pp.- |
| #Pages | 8 |
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