PSB
2008
13 years 6 months ago
2008
bstracts in the structure prior of a Bayesian network could improve the prediction of the prognosis in cancer. Our results show that prediction of the outcome with the text prior w...
NIPS
2008
13 years 6 months ago
2008
Many interesting problems, including Bayesian network structure-search, can be cast in terms of finding the optimum value of a function over the space of graphs. However, this fun...
ICMLA
2007
13 years 6 months ago
2007
We introduce a polynomial-time algorithm to learn Bayesian networks whose structure is restricted to nodes with in-degree at most k and to edges consistent with the optimal branch...
ETFA
2008
IEEE
13 years 6 months ago
2008
IEEE
Microshrinkages are known as probably the most difficult defects to avoid in high-precission foundry. Depending on the magnitude of this defect, the piece in which it appears must...
FLAIRS
2008
13 years 6 months ago
2008
One of the major weaknesses of current research on the Semantic Web (SW) is the lack of proper means to represent and reason with uncertainty. A number of recent efforts from the ...
FLAIRS
2008
13 years 6 months ago
2008
An efficient framework is proposed for the fast recovery of Bayesian network classifier. A novel algorithm, called Iterative Parent-Child learningBayesian Network Classifier (IPC-...
FLAIRS
2007
13 years 6 months ago
2007
In this paper, we study the problem of information preservation when decomposing a single Bayesian network into a set of smaller Bayesian networks. We present a method that lossle...
AAAI
2008
13 years 6 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...
EKAW
2006
Springer
13 years 8 months ago
2006
Springer
Abstract. This paper concerns the iterative implementation of a knowledge model in a data mining context. Our approach relies on coupling a Bayesian network design with an associat...
ECTEL
2006
Springer
13 years 8 months ago
2006
Springer
Bayesian networks are commonly used in cognitive student modeling and assessment. They typically represent the item-concepts relationships, where items are observable responses to ...