The efficient execution of irregular parallel applications on shared distributed systems requires novel approaches to scheduling, since both the application requirements and the sy...
In this paper we present decomposable priors, a family of priors over structure and parameters of tree belief nets for which Bayesian learning with complete observations is tracta...
The likelihood for patterns of continuous attributes for the naive Bayesian classifier (NBC) may be approximated by kernel density estimation (KDE), letting every pattern influenc...
Abstract. We present a new method for voting exponential (in the number of attributes) size sets of Bayesian classifiers in polynomial time with polynomial memory requirements. Tra...
We study the detection performance of large scale sensor networks, configured as trees with bounded height, in which information is progressively compressed as it moves towards th...