106 search results - page 16 / 22 » The max-min hill-climbing Bayesian network structure learnin... |
ICML
2008
IEEE
15 years 10 months ago
2008
IEEE
We propose Laplace max-margin Markov networks (LapM3 N), and a general class of Bayesian M3 N (BM3 N) of which the LapM3 N is a special case with sparse structural bias, for robus...
FLAIRS
2004
14 years 11 months ago
2004
We propose a new approach for learning Bayesian classifiers from data. Although it relies on traditional Bayesian network (BN) learning algorithms, the effectiveness of our approa...
JMLR
2000
14 years 9 months ago
2000
This paper describes the mixtures-of-trees model, a probabilistic model for discrete multidimensional domains. Mixtures-of-trees generalize the probabilistic trees of Chow and Liu...
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CORR
2011
Springer
14 years 1 months ago
2011
Springer
We propose a logical/mathematical framework for statistical parameter learning of parameterized logic programs, i.e. de nite clause programs containing probabilistic facts with a ...
BMCBI
2006
14 years 9 months ago
2006
Background: A central goal of molecular biology is to understand the regulatory mechanisms of gene transcription and protein synthesis. Because of their solid basis in statistics,...