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» Compiling Bayesian Networks Using Variable Elimination
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UAI
2000
13 years 9 months ago
Gaussian Process Networks
In this paper we address the problem of learning the structure of a Bayesian network in domains with continuous variables. This task requires a procedure for comparing different c...
Nir Friedman, Iftach Nachman
ICDM
2003
IEEE
158views Data Mining» more  ICDM 2003»
14 years 25 days ago
Identifying Markov Blankets with Decision Tree Induction
The Markov Blanket of a target variable is the minimum conditioning set of variables that makes the target independent of all other variables. Markov Blankets inform feature selec...
Lewis Frey, Douglas H. Fisher, Ioannis Tsamardinos...
CEC
2010
IEEE
13 years 4 months ago
Evolved Bayesian Network models of rig operations in the gulf of Mexico
The operation of drilling rigs is highly expensive. It is therefore important to be able to identify and analyse variables affecting rig operations. We investigate the use of Genet...
François A. Fournier, John A. W. McCall, An...
ICPR
2006
IEEE
14 years 8 months ago
Switching Auxiliary Chains for Speech Recognition based on Dynamic Bayesian Networks
This paper investigates the problem of incorporating auxiliary information (e.g. pitch) for speech recognition using dynamic Bayesian networks (DBNs). Previous works usually model...
Hui Lin 0001, Zhijian Ou
ADMA
2006
Springer
121views Data Mining» more  ADMA 2006»
14 years 1 months ago
A New Polynomial Time Algorithm for Bayesian Network Structure Learning
We propose a new algorithm called SCD for learning the structure of a Bayesian network. The algorithm is a kind of constraintbased algorithm. By taking advantage of variable orderi...
Sanghack Lee, Jihoon Yang, Sungyong Park