We consider the problem of learning the parameters of a Bayesian network from data, while taking into account prior knowledge about the signs of influences between variables. Such...
The paper presents a novel strategy aimed at modelling instruction energy consumption of 32-bits microprocessors. Differently from former approaches, the proposed instruction-level...
Carlo Brandolese, Fabio Salice, William Fornaciari...
Several theoretical methods have been developed in the past years to evaluate the generalization ability of a classifier: they provide extremely useful insights on the learning ph...
In this paper we present a method for the integration of nonlinear holonomic constraints in deformable models and its application to the problems of shape and illuminant direction...
SyncProbe improves the end-to-end predictability of distributed systems by providing applications with a real-time estimate of the maximum expected message delay (upper bound on c...