Presentation | 2004/6/18 Nonlinear noisy independent component analysis Shin-ichi MAEDA, Shin ISHII, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | In this study, we discuss a noisy nonlinear extension of independent component analysis (ICA). There have been proposed several extensions of the original noise-free linear ICA, e. g., noisy ICA or nonlinear ICA. There are few studies dealing with both noisy and nonlinear situations, however, because of the difficulty in integral calculation of the likelihood. In this study, we approximate the integral by a Taylor expansion and a Laplace approximation. The derived algorithm formulated as an expectation-maximization (EM) algorithm generalizes several of existing ICA algorithms. We also derive an optimal step size for our EM algorithm and discuss the reason why various noisy linear ICA algorithms based on maximum likelihood estimation are unsuccessful in being the noise-free linear ICA in the noiseless limit. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | independent component analysis / nonlinear mixture / Laplace approximation / EM algorithm |
Paper # | NC2004-35 |
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Committee | NC |
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Conference Date | 2004/6/18(1days) |
Place (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) | Nonlinear noisy independent component analysis |
Sub Title (in English) | |
Keyword(1) | independent component analysis |
Keyword(2) | nonlinear mixture |
Keyword(3) | Laplace approximation |
Keyword(4) | EM algorithm |
1st Author's Name | Shin-ichi MAEDA |
1st Author's Affiliation | Nara Institute of Science and Technology() |
2nd Author's Name | Shin ISHII |
2nd Author's Affiliation | Nara Institute of Science and Technology |
Date | 2004/6/18 |
Paper # | NC2004-35 |
Volume (vol) | vol.104 |
Number (no) | 140 |
Page | pp.pp.- |
#Pages | 6 |
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