106 search results - page 10 / 22 » The max-min hill-climbing Bayesian network structure learnin... |
81
Voted
AI
2002
Springer
14 years 9 months ago
2002
Springer
This paper provides algorithms that use an information-theoretic analysis to learn Bayesian network structures from data. Based on our three-phase learning framework, we develop e...
UAI
2003
14 years 11 months ago
2003
This paper considers a method that combines ideas from Bayesian learning, Bayesian network inference, and classical hypothesis testing to produce a more reliable and robust test o...
ECSQARU
2005
Springer
15 years 3 months ago
2005
Springer
In this paper we explore the use of several types of structural restrictions within algorithms for learning Bayesian networks. These restrictions may codify expert knowledge in a g...
IJAR
2010
14 years 8 months ago
2010
Probabilistic Decision Graphs (PDGs) are a class of graphical models that can naturally encode some context specific independencies that cannot always be efficiently captured by...
CIDM
2009
IEEE
15 years 4 months ago
2009
IEEE
Abstract— A Bayes net has qualitative and quantitative aspects: The qualitative aspect is its graphical structure that corresponds to correlations among the variables in the Baye...