We show that for even quasi-concave objective functions the worst-case distribution, with respect to a family of unimodal distributions, of a stochastic programming problem is a u...
This paper develops a variant of Simulated Annealing (SA) algorithm for solving discrete stochastic optimization problems where the objective function is stochastic and can be eva...
This paper deals with value (and Q-) function approximation in deterministic Markovian decision processes (MDPs). A general statistical framework based on the Kalman filtering pa...
This paper describes a distributed algorithm for Boolean function manipulation. The algorithm is based on Binary Decision Diagrams (BDDs), which are one of the most commonly used ...
F. Bianchi, Fulvio Corno, Maurizio Rebaudengo, Mat...
This work presents a formal probabilistic approach for solving optimization problems in design automation. Prediction accuracy is very low especially at high levels of design flo...