106 search results - page 18 / 22 » The max-min hill-climbing Bayesian network structure learnin... |
JMLR
2006
14 years 9 months ago
2006
We study the computational and sample complexity of parameter and structure learning in graphical models. Our main result shows that the class of factor graphs with bounded degree...
KDD
2003
ACM
15 years 10 months ago
2003
ACM
Data Mining with Bayesian Network learning has two important characteristics: under broad conditions learned edges between variables correspond to causal influences, and second, f...
72
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GECCO
2006
Springer
15 years 1 months ago
2006
Springer
Recently, studies with the XCS classifier system on Boolean functions have shown that in certain types of functions simple crossover operators can lead to disruption and, conseque...
107
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AI
2010
Springer
14 years 9 months ago
2010
Springer
Bayesian networks (BNs) are used to represent and ef ciently compute with multi-variate probability distributions in a wide range of disciplines. One of the main approaches to per...
101
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BMCBI
2007
14 years 9 months ago
2007
Background: In vertebrates, a large part of gene transcriptional regulation is operated by cisregulatory modules. These modules are believed to be regulating much of the tissue-sp...