Asynchronous method calls have been proposed to better integrate object orientation with distribution. In the Creol language, asynchronous method calls are combined with so-called...
In many domains, a Bayesian network's topological structure is not known a priori and must be inferred from data. This requires a scoring function to measure how well a propo...
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...
One problem faced in knowledge engineering for Bayesian networks is the exponential growth of the number of parameters in their conditional probability tables (CPTs). The most comm...
Bayesian network models are widely used for discriminative prediction tasks such as classification. Usually their parameters are determined using 'unsupervised' methods ...