In this paper, we introduce a new restricted Bayesian network classifier that extends naive Bayes by relaxing the conditional independence assumptions, and show that it is partly ...
Autonomous agents that communicate using probabilistic information and use Bayesian networks for knowledge representation need an update mechanism that goes beyond conditioning on ...
Previous work on context-specific independence in Bayesian networks is driven by a common goal, namely to represent the conditional probability tables in a most compact way. In th...
In several domains it is common to have data from different, but closely related problems. For instance, in manufacturing, many products follow the same industrial process but with...
Roger Luis, Luis Enrique Sucar, Eduardo F. Morales
Abstract—It is well known that for finite-sized networks, onestep retrieval in the autoassociative Willshaw net is a suboptimal way to extract the information stored in the syna...