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» The Representational Power of Discrete Bayesian Networks
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ICDM
2005
IEEE
116views Data Mining» more  ICDM 2005»
13 years 11 months ago
Learning Functional Dependency Networks Based on Genetic Programming
Bayesian Network (BN) is a powerful network model, which represents a set of variables in the domain and provides the probabilistic relationships among them. But BN can handle dis...
Wing-Ho Shum, Kwong-Sak Leung, Man Leung Wong
ICML
2004
IEEE
14 years 6 months ago
Learning Bayesian network classifiers by maximizing conditional likelihood
Bayesian networks are a powerful probabilistic representation, and their use for classification has received considerable attention. However, they tend to perform poorly when lear...
Daniel Grossman, Pedro Domingos
IBERAMIA
1998
Springer
13 years 10 months ago
Bayesian Networks for Reliability Analysis of Complex Systems
This paper presents an extension of Bayesian networks (BN) applied to reliability analysis. We developed a general methodology for modelling reliability of complex systems based o...
José G. Torres-Toledano, Luis Enrique Sucar
BMCBI
2008
201views more  BMCBI 2008»
13 years 5 months ago
A copula method for modeling directional dependence of genes
Background: Genes interact with each other as basic building blocks of life, forming a complicated network. The relationship between groups of genes with different functions can b...
Jong-Min Kim, Yoon-Sung Jung, Engin A. Sungur, Kap...
ICRA
2008
IEEE
150views Robotics» more  ICRA 2008»
14 years 6 days ago
Rigorously Bayesian range finder sensor model for dynamic environments
— This paper proposes and experimentally validates a Bayesian network model of a range finder adapted to dynamic environments. The modeling rigorously explains all model assumpt...
Tinne De Laet, Joris De Schutter, Herman Bruyninck...