We propose a variance-component probabilistic model for sparse signal reconstruction and model selection. The measurements follow an underdetermined linear model, where the unknown...
Developing an optimizing compiler for a newly proposed architecture is extremely difficult when there is only a simulator of the machine available. Designing such a compiler requ...
John Cavazos, Christophe Dubach, Felix V. Agakov, ...
Modelling activities in molecular biology face the difficulty of prediction to link molecular knowledge with cell phenotypes. Even when the interaction graph between molecules is k...
This paper presents an approach to artificial intelligence planning based on linear temporal logic (LTL). A simple and easy-to-use planning language is described, PDDL-K (Planning...
Marta Cialdea Mayer, Carla Limongelli, Andrea Orla...
We describe our real time decision support system; a system that supports information gathering and managing of an investment portfolio. Our system uses the Object Oriented Bayesi...