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137
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IJCAI
2007
15 years 4 months ago
Compiling Bayesian Networks Using Variable Elimination
Compiling Bayesian networks has proven an effective approach for inference that can utilize both global and local network structure. In this paper, we define a new method of comp...
Mark Chavira, Adnan Darwiche
126
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CVPR
1999
IEEE
16 years 4 months ago
Vision-Based Speaker Detection Using Bayesian Networks
The development of user interfaces based on vision and speech requires the solution of a challenging statistical inference problem: The intentions and actions of multiple individu...
James M. Rehg, Kevin P. Murphy, Paul W. Fieguth
113
Voted
ICPR
2008
IEEE
16 years 3 months ago
Exploiting qualitative domain knowledge for learning Bayesian network parameters with incomplete data
When a large amount of data are missing, or when multiple hidden nodes exist, learning parameters in Bayesian networks (BNs) becomes extremely difficult. This paper presents a lea...
Qiang Ji, Wenhui Liao
107
Voted
ICML
2007
IEEE
16 years 3 months ago
Parameter learning for relational Bayesian networks
We present a method for parameter learning in relational Bayesian networks (RBNs). Our approach consists of compiling the RBN model into a computation graph for the likelihood fun...
Manfred Jaeger
157
Voted
ICML
2005
IEEE
16 years 3 months ago
Efficient discriminative learning of Bayesian network classifier via boosted augmented naive Bayes
The use of Bayesian networks for classification problems has received significant recent attention. Although computationally efficient, the standard maximum likelihood learning me...
Yushi Jing, Vladimir Pavlovic, James M. Rehg