In this paper, we extend the QMR-DT probabilistic model for the domain of internal medicine to include decisions about treatments. In addition, we describe how we can use the comp...
In this paper we propose a new approach to probabilistic inference on belief networks, global conditioning, which is a simple generalization of Pearl's (1986b) method of loop...
Ross D. Shachter, Stig K. Andersen, Peter Szolovit...
We examine the notion of "unrelatedness" in a probabilistic framework. Three formulations are presented. In the first formulation, two variables a and b are totally inde...
The intelligent reformulation or restructuring of a belief network can greatly increase the efficiency of inference. However, time expended for reformulation is not available for ...
This paper is about the use of metric data structures in high-dimensionalor non-Euclidean space to permit cached sufficientstatisticsaccelerationsof learning algorithms. It has re...