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Document type:
Zeitschriftenaufsatz
Author(s):
Drton, Mathias; Richardson, Thomas S.
Title:
A New Algorithm for Maximum Likelihood Estimation in Gaussian Graphical Models for Marginal Independence
Abstract:
Graphical models with bi-directed edges (<->) represent marginal independence: the absence of an edge between two vertices indicates that the corresponding variables are marginally independent. In this paper, we consider maximum likelihood estimation in the case of continuous variables with a Gaussian joint distribution, sometimes termed a covariance graph model. We present a new fitting algorithm which exploits standard regression techniques and establish its convergence properties. Moreover, we contrast our procedure to existing estimation methods
Dewey Decimal Classification:
510 Mathematik
Congress title:
19th Conference on Uncertainty in Artificial Intelligence (UAI 2003)
Congress / additional information:
August 7-10, 2003; Acapulco, Mexico
Journal title:
Proceedings of the 19th Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-03)
Year:
2003
Pages contribution:
184-191
Language:
en
WWW:
UAI
Publisher:
Morgan Kaufmann
Publisher address:
San Francisco, CA, USA
Print-ISSN:
0-127-05664-5
Format:
Text
 BibTeX