This paper considers the problem of knowledgebased model construction in the presence of uncertainty about the association of domain entities to random variables. Multi-entity Bay...
This paper addresses one of the fundamental problems encountered in performance prediction for object recognition. In particular we address the problems related to estimation of s...
Background: Hidden Markov Models (HMMs) have proven very useful in computational biology for such applications as sequence pattern matching, gene-finding, and structure prediction...
: We develop and study the concept of dataflow process networks as used for example by Kahn to suit exact computation over data types related to real numbers, such as continuous fu...
We propose an novel method of computing and storing DataCubes. Our idea is to use Bayesian Networks, which can generate approximate counts for any query combination of attribute v...