1340 search results - page 89 / 268 » Structure learning of Bayesian networks using constraints |
ICML
2010
IEEE
15 years 28 days ago
2010
IEEE
The structure of a Markov network is typically learned using top-down search. At each step, the search specializes a feature by conjoining it to the variable or feature that most ...
BMCBI
2010
14 years 6 months ago
2010
Background: Differential co-expression analysis is an emerging strategy for characterizing disease related dysregulation of gene expression regulatory networks. Given pre-defined ...
RECOMB
2007
Springer
16 years 5 days ago
2007
Springer
Abstract. An important problem in biology is to understand correspondences between mRNA microarray levels and mass spectrometry peptide counts. Recently, a compendium of mRNA expre...
AAAI
2006
15 years 1 months ago
2006
The MAP (maximum a posteriori hypothesis) problem in Bayesian networks is to find the most likely states of a set of variables given partial evidence on the complement of that set...
AAAI
2008
15 years 2 months ago
2008
Probabilistic modeling has been a dominant approach in Machine Learning research. As the field evolves, the problems of interest become increasingly challenging and complex. Makin...