Abstract. In supervised learning, discretization of the continuous explanatory attributes enhances the accuracy of decision tree induction algorithms and naive Bayes classifier. M...
Background: The models developed to characterize the evolution of multigene families (such as the birth-and-death and the concerted models) have also been applied on the level of ...
iLTL is a probabilistic temporal logic that can specify properties of multiple discrete time Markov chains (DTMCs). In this paper, we describe two related tools: MarkovEstimator a...
—Methods for learning decision rules are being successfully applied to many problem domains, especially where understanding and interpretation of the learned model is necessary. ...
Clock distribution is one of the key limiting factors in any high speed, sub-100nm VLSI design. Unwanted clock skews, caused by variation effects like manufacturing variations, po...