This paper investigates a class of learning problems called learning satisfiability (LSAT) problems, where the goal is to learn a set in the input (feature) space that satisfies...
Frederic Thouin, Mark Coates, Brian Eriksson, Robe...
What happens to the optimal interpretation of noisy data when there exists more than one equally plausible interpretation of the data? In a Bayesian model-learning framework the a...
Today's data centers offer IT services mostly hosted on dedicated physical servers. Server virtualization provides a technical means for server consolidation. Thus, multiple v...
The process of creating e-learning contents using reusable learning objects (LOs) can be broken down in two sub-processes: LOs finding and LO sequencing. Sequencing is usually per...
In this paper, we study model checking of timed automata (TAs), and more precisely we aim at finding efficient model checking for subclasses of TAs. For this, we consider model ch...