Objective Bayesian probability is often defined over rather simple domains, e.g., finite event spaces or propositional languages. This paper investigates the extension of objectiv...
In this paper we investigate the modulation domain as an alternative to the acoustic domain for speech enhancement. More specifically, we wish to determine how competitive the mo...
This paper shows how computational Riemannian manifold can be used to solve several problems in computer vision and graphics. Indeed, Voronoi segmentations and Delaunay graphs comp...
Motivation: Extracting functional information from protein–protein interactions (PPI) poses significant challenges arising from the noisy, incomplete, generic and static nature...
Temporal difference reinforcement learning algorithms are perfectly suited to autonomous agents because they learn directly from an agent’s experience based on sequential actio...