Abstract. Performance of real-time applications on network communication channels are strongly related to losses and temporal delays. Several studies showed that these network feat...
Pierluigi Salvo Rossi, Francesco Palmieri, Giulio ...
This paper presents a general and efficient framework for probabilistic inference and learning from arbitrary uncertain information. It exploits the calculation properties of fini...
This article deals with the identification of gene regulatory networks from experimental data using a statistical machine learning approach. A stochastic model of gene interactio...
In functional Magnetic Resonance Imaging (fMRI), recent works have addressed the non parametric estimation of the Hemodynamic Response Function (HRF) under linearity and stationar...
Sophie Donnet, Marc Lavielle, Philippe Ciuciu, Jea...
Bayesian Kullback Ying—Yang dependence reduction system and theory is presented. Via stochastic approximation, implementable algorithms and criteria are given for parameter lear...