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FLAIRS
2009
13 years 9 months ago
A Comparative Study of Variable Elimination and Arc Reversal in Bayesian Network Inference
We compare two approaches to Bayesian network inference, called variable elimination (VE) and arc reversal (AR). It is established that VE never requires more space than AR, and n...
Cory J. Butz, Junying Chen, Ken Konkel, Pawan Ling...
ATAL
2008
Springer
14 years 1 months ago
Efficient approximate inference in distributed Bayesian networks for MAS-based sensor interpretation
The multiply sectioned Bayesian network (MSBN) framework is the most studied approach for distributed Bayesian Network inference in an MAS setting. This paper describes a new fram...
Norman Carver
ICML
2005
IEEE
15 years 10 days ago
Naive Bayes models for probability estimation
Naive Bayes models have been widely used for clustering and classification. However, they are seldom used for general probabilistic learning and inference (i.e., for estimating an...
Daniel Lowd, Pedro Domingos