We present a refinement and a coarsening (also simplification or decimation) algorithm for the adaptive representation of bivariate functions. The algorithms have proved to be eff...
Many processes are composed of a n-fold repetition of some simpler process. If the whole process can be modeled with a neural network, we present a method to derive a model of the...
Decision theory does not traditionally include uncertainty over utility functions. We argue that the a person's utility value for a given outcome can be treated as we treat o...
We present a time–parallel technique for the fast generation of self–similar traffic which is suitable for performance studies of Asynchronous Transfer Mode (ATM) networks. Th...
Ioanis Nikolaidis, C. Anthony Cooper, Kalyan S. Pe...
In this paper we examine a novel addition to the known methods for learning Bayesian networks from data that improves the quality of the learned networks. Our approach explicitly ...