In this paper, we highlight a fast, effective and practical statistical approach that deals with inter and intra-die variations in VLSI chips. Our methodology is applied to a numb...
Bayesian networks provide a modeling language and associated inference algorithm for stochastic domains. They have been successfully applied in a variety of medium-scale applicati...
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...
A compositional method for estimating software reliability of many threaded programs is developed. The method uses estimates of the reliability of individual modules and the proba...
Abstract. Monads are a well-established tool for modelling various computational effects. They form the semantic basis of Moggi’s computational metalanguage, the metalanguage of ...