175 search results - page 10 / 35 » Learning Continuous Time Bayesian Networks |
KDD
2002
ACM
14 years 8 months ago
2002
ACM
In this paper we propose a scaling-up method that is applicable to essentially any induction algorithm based on discrete search. The result of applying the method to an algorithm ...
GECCO
2009
Springer
14 years 10 days ago
2009
Springer
We propose a cooperative-coevolution – Parisian trend – algorithm, IMPEA (Independence Model based Parisian EA), to the problem of Bayesian networks structure estimation. It i...
ICML
2009
IEEE
14 years 8 months ago
2009
IEEE
AODE (Aggregating One-Dependence Estimators) is considered one of the most interesting representatives of the Bayesian classifiers, taking into account not only the low error rate...
UAI
2001
13 years 9 months ago
2001
The search space of Bayesian Network structures is usually defined as Acyclic Directed Graphs (DAGs) and the search is done by local transformations of DAGs. But the space of Baye...
CEC
2010
IEEE
13 years 8 months ago
2010
IEEE
Learning Bayesian networks from data is an N-P hard problem with important practical applications. Several researchers have designed algorithms to overcome the computational comple...