This paper addresses exact learning of Bayesian network structure from data and expert's knowledge based on score functions that are decomposable. First, it describes useful ...
Many existing explanation methods in Bayesian networks, such as Maximum a Posteriori (MAP) assignment and Most Probable Explanation (MPE), generate complete assignments for target...
Abstract. The Bayesian approach to machine learning amounts to inferring posterior distributions of random variables from a probabilistic model of how the variables are related (th...
Robust, real-time tracking of objects from visual data requires probabilistic fusion of multiple visual cues. Previous approaches have either been ad hoc or relied on a Bayesian n...
Abstract. Objective: Age classification of patients based on information extracted from electrocardiograms (ECG's). The scope of this work is to develop and compare the perfor...
M. Wiggins, A. Saad, Brian Litt, George J. Vachtse...