145 search results - page 22 / 29 » Bayesian Network Learning with Parameter Constraints |
EWSN
2004
Springer
15 years 9 months ago
2004
Springer
Wireless sensor networks typically consist of a large number of sensor nodes embedded in a physical space. Such sensors are low-power devices that are primarily used for monitoring...
ICML
2003
IEEE
15 years 10 months ago
2003
IEEE
The use of domain knowledge in a learner can greatly improve the models it produces. However, high-quality expert knowledge is very difficult to obtain. Traditionally, researchers...
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ECML
2006
Springer
15 years 1 months ago
2006
Springer
Causal independence modelling is a well-known method both for reducing the size of probability tables and for explaining the underlying mechanisms in Bayesian networks. In this pap...
RECOMB
2003
Springer
15 years 9 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...
ECSQARU
2001
Springer
15 years 2 months ago
2001
Springer
Abstract. The K2 metric is a well-known evaluation measure (or scoring function) for learning Bayesian networks from data [7]. It is derived by assuming uniform prior distributions...