We describe a Markov chain Monte Carlo (MCMC)-based algorithm for sampling solutions to mixed Boolean/integer constraint problems. The focus of this work differs in two points from...
Abstract. Adaptive consistency is a solving algorithm for constraint networks. Its basic step is variable elimination: it takes a network as input, and producesan equivalent networ...
Abstract. Although Constraint Programming (CP) is considered a useful tool for tackling combinatorial problems, its lack of flexibility when dealing with uncertainties and prefere...
Alberto Delgado, Carlos Alberto Olarte, Jorge Andr...
Mining frequent itemsets is a popular method for finding associated items in databases. For this method, support, the co-occurrence frequency of the items which form an associatio...
We consider in this paper how to leverage heterogeneous mobile computing capability for efficient processing of real-time range-monitoring queries. In our environment, each mobil...