Presentation 2003/1/28
Dynamics of the deterministic annealing EM algorithm extended by means of non-extensive statistical mechanics
Jun-ichi INOUE, Katsumi TABUSHI,
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Abstract(in English) We extend the EM algorithm to overcome its bottleneck, that is to say, the problem of local maxima of the marginal likelihood due to its strong dependence of initial conditions. As an alternative posterior distribution appearing in the so-called Q-function, we use the distribution that maximizes the non-extensive Tsallis entropy. The distribution we introduce has a parameter q which represents the non-extensivity of the entropy. We control the parameter q so as to weaken the influence of the initial conditions. In order to investigate its performance, we apply our algorithm to Gaussian mixture estimation problems under some additive noises. In large data limit, we derive the averaged update equations w. r. t. hyper-parameters, marginal likelihood etc. analytically. Our analysis supports usefulness of our algorithm.
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Keyword(in English) EM algorithm / Maximum likelihood estimate / Non-extensive statistical mechanics / Tsallis entropy / Gaussian mixture
Paper # NC2002-126
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Committee NC
Conference Date 2003/1/28(1days)
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Language JPN
Title (in Japanese) (See Japanese page)
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Title (in English) Dynamics of the deterministic annealing EM algorithm extended by means of non-extensive statistical mechanics
Sub Title (in English)
Keyword(1) EM algorithm
Keyword(2) Maximum likelihood estimate
Keyword(3) Non-extensive statistical mechanics
Keyword(4) Tsallis entropy
Keyword(5) Gaussian mixture
1st Author's Name Jun-ichi INOUE
1st Author's Affiliation Graduate School of Engineering, Hokkaido University()
2nd Author's Name Katsumi TABUSHI
2nd Author's Affiliation Graduate School of Engineering, Hokkaido University
Date 2003/1/28
Paper # NC2002-126
Volume (vol) vol.102
Number (no) 628
Page pp.pp.-
#Pages 6
Date of Issue