-- Most optimization algorithms that use probabilistic models focus on extracting the information from good solutions found in the population. A selection method discards the below...
Abstract. Authors extend the multi-parameter attacktree model to include inaccurate or estimated parameter values, which are modelled as probabilistic interval estimations. The pap...
We develop a probabilistic criterion for belief expansion that is sensitive to the degree of contextual fit of the new information to our belief set as well as to the reliability...
This paper presents a method of generating Mercer Kernels from an ensemble of probabilistic mixture models, where each mixture model is generated from a Bayesian mixture density e...
For centuries, scholars have explored the deep links among human languages. In this paper, we present a class of probabilistic models that use these links as a form of naturally o...