This paper investigates the effects of demand risk on the performance of supply chain in continuous time setting. The inventory level has been modeled as a jump-diffusion process ...
Abstract. Two approaches have been used to perform approximate inference in Bayesian networks for which exact inference is infeasible: employing an approximation algorithm, or appr...
Finding the sparsest solution for an under-determined linear system of equations D = s is of interest in many applications. This problem is known to be NP-hard. Recent work studie...
Program analysis and optimizationcan be speeded upthrough the use of the dependence flow graph (DFG), a representation of program dependences which generalizes def-use chains and...
The performance of Artificial Neural Networks is largely influenced by the value of their parameters. Among these free parameters, one can mention those related with the network a...