18 search results - page 2 / 4 » A new hybrid method for Bayesian network learning With depen... |
ICPR
2008
IEEE
13 years 11 months ago
2008
IEEE
This paper describes a new approach to unify constraints on parameters with training data to perform parameter estimation in Bayesian networks of known structure. The method is ge...
BMCBI
2010
13 years 4 months ago
2010
Background: Identifying candidate genes in genetic networks is important for understanding regulation and biological function. Large gene expression datasets contain relevant info...
UAI
2003
13 years 5 months ago
2003
Methods for learning Bayesian networks can discover dependency structure between observed variables. Although these methods are useful in many applications, they run into computat...
ECCV
2008
Springer
14 years 6 months ago
2008
Springer
Probabilistic graphical models such as Bayesian Networks have been increasingly applied to many computer vision problems. Accuracy of inferences in such models depends on the quali...
JMLR
2010
12 years 11 months ago
2010
We propose to solve the combinatorial problem of finding the highest scoring Bayesian network structure from data. This structure learning problem can be viewed as an inference pr...