We study probabilistic inference in large, layered Bayesian networks represented as directed acyclic graphs. We show that the intractability of exact inference in such networks do...
We consider how simulation metamodels can be used to optimize the performance of a system that depends on a number of factors. We focus on the situation where the number of simula...
This paper proposes a ranking method to exploit statistical correlations among pairs of attribute values in relational databases. For a given query, the correlations of the query ...
We propose a new family of Bayesian estimators for speech enhancement where the cost function includes both a power law and a weighting factor. The parameters of the cost function,...
Thewidespreaduse of influence diagramsto represent andsolve Bayesiandecision problemsis still limited by the inflexibility andrather restrictive semanticsof influence diagrams. In...