DocumentCode :
2552674
Title :
Convergence Analysis of the EM Algorithm and Joint Minimization of Free Energy
Author :
Maeda, Shin-ichi ; Ishii, Shin
Author_Institution :
Nara Inst. of Sci. & Technol., Nara
fYear :
2007
fDate :
27-29 Aug. 2007
Firstpage :
318
Lastpage :
323
Abstract :
Although the expectation-maximization (EM) algorithm has been popularly used for its computational convenience, it has been recognized that the EM algorithm works slowly in certain situations. In this study, we analyze the convergence property of the EM algorithm in terms of the minimization of the free energy, and show that the slow convergence is due to the optimization method of the free energy. The analyses suggest a different optimization can be appropriate for situations of slow convergence. Then, we propose a new speeding-up method for optimization of the free energy. The validity of the new method is confirmed by using a simple problem.
Keywords :
convergence; expectation-maximisation algorithm; optimisation; convergence analysis; expectation-maximization algorithm; free energy joint minimization; Algorithm design and analysis; Convergence; Information analysis; Iterative algorithms; Maximum likelihood estimation; Minimization methods; Optimization methods; Random variables; Statistics; Yttrium;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning for Signal Processing, 2007 IEEE Workshop on
Conference_Location :
Thessaloniki
ISSN :
1551-2541
Print_ISBN :
978-1-4244-1566-3
Electronic_ISBN :
1551-2541
Type :
conf
DOI :
10.1109/MLSP.2007.4414326
Filename :
4414326
Link To Document :
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