564 search results - page 2 / 113 » Approximation algorithms for restricted Bayesian network str... |
UAI
1998
13 years 6 months ago
1998
In recent years there has been a flurry of works on learning Bayesian networks from data. One of the hard problems in this area is how to effectively learn the structure of a beli...
GECCO
2007
Springer
13 years 11 months ago
2007
Springer
Bayesian Networks are today used in various fields and domains due to their inherent ability to deal with uncertainty. Learning Bayesian Networks, however is an NP-Hard task [7]....
ECAI
2008
Springer
13 years 7 months ago
2008
Springer
Abstract. Two approaches have been used to perform approximate inference in Bayesian networks for which exact inference is infeasible: employing an approximation algorithm, or appr...
NIPS
1998
13 years 6 months ago
1998
Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...
IICAI
2003
13 years 6 months ago
2003
Abstract. We introduce a new genetic algorithm approach for learning a Bayesian network structure from data. Our method is capable of learning over all node orderings and structure...