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Abstract: The Expectation-Maximization (EM) algorithm is an iterative approach to maximum likelihood parameter estimation. Jordan and Jacobs (1993) recently proposed an EM algorithm for the mixture of experts architecture of Jacobs, Jordan, Nowlan and Hinton (1991) and the hierarchical mixture of experts architecture of Jordan and Jacobs (1992). They showed empirically that the EM algorithm for these architectures yields significantly faster convergence than gradient ascent. In the current paper we... (Update)
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BibTeX entry: (Update)
Jordan, MI & Xu, L (1993). Convergence Results for the EM Approach to Mixtures of Experts Architectures. CBCL Memo 87, Centre for Biological and Computational Learning, MIT. http://citeseer.ist.psu.edu/article/jordan93convergence.html More
@techreport{ jordan93convergence,
author = "Michael I. Jordan and Lei Xu",
title = "Convergence Results for the {EM} Approach to Mixtures of Experts Architectures",
number = "AIM-1458",
pages = "33",
year = "1993",
url = "citeseer.ist.psu.edu/article/jordan93convergence.html" }
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