25 search results - page 2 / 5 » Learning Bounded Treewidth Bayesian Networks |
JMLR
2010
12 years 11 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
13 years 7 months 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 6 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
13 years 9 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 5 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...