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» The Representational Power of Discrete Bayesian Networks
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ICDM
2005
IEEE
116views Data Mining» more  ICDM 2005»
15 years 3 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
15 years 10 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
15 years 1 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»
14 years 9 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»
15 years 3 months 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...