25 search results - page 2 / 5 » Learning Bounded Treewidth Bayesian Networks |
JMLR
2010
13 years 4 months ago
2010
We introduce a simple order-based greedy heuristic for learning discriminative structure within generative Bayesian network classifiers. We propose two methods for establishing an...
AAAI
2008
14 years 3 days ago
2008
Modern Bayesian Network learning algorithms are timeefficient, scalable and produce high-quality models; these algorithms feature prominently in decision support model development...
UAI
2008
13 years 11 months ago
2008
Graphical models are usually learned without regard to the cost of doing inference with them. As a result, even if a good model is learned, it may perform poorly at prediction, be...
NN
1997
Springer
14 years 1 months ago
1997
Springer
Bayesian networks are directed acyclic graphs that represent dependencies between variables in a probabilistic model. Many time series models, including the hidden Markov models (H...
RECOMB
2003
Springer
14 years 10 months ago
2003
Springer
Genetic linkage analysis is a challenging application which requires Bayesian networks consisting of thousands of vertices. Consequently, computing the likelihood of data, which i...