In this paper, we describe a decompositional approach to convergence proofs for stochastic hybrid systems given as probabilistic hybrid automata. We focus on a concept called “st...
This paper addresses the problem of learning from highly structured data. Speci cally, it describes a procedure, called decomposition, that allows a learner to access automatically...
— Partially Observable Markov Decision Processes (POMDPs) offer a powerful mathematical framework for making optimal action choices in noisy and/or uncertain environments, in par...
Abstract The G12 project is developing a software environment for stating and solving combinatorial problems by mapping a high-level model of the problem to an efficient combinatio...
Jakob Puchinger, Peter J. Stuckey, Mark G. Wallace...
To be efficient, data protection algorithms should generally exploit the properties of the media information in the transform domain. In this paper, we will advocate the use of no...
Philippe Jost, Pierre Vandergheynst, Pascal Frossa...