106 search results - page 16 / 22 » The max-min hill-climbing Bayesian network structure learnin... |
ICML
2008
IEEE
16 years 13 days 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
15 years 1 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...
79
Voted
JMLR
2000
14 years 11 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...
126
Voted
CORR
2011
Springer
14 years 3 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 ...
94
Voted
BMCBI
2006
14 years 11 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,...