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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