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...
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...
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...