Bayesian learning in undirected graphical models--computing posterior distributions over parameters and predictive quantities-is exceptionally difficult. We conjecture that for ge...
We consider optimization problems of the form (S, cost), where S is a clause set over Boolean variables x1 . . . xn, with an arbitrary cost function cost: Bn → R, and the aim is ...
Javier Larrosa, Robert Nieuwenhuis, Albert Olivera...
This paper reports on a new approach to solving a subset-based points-to analysis for Java using Binary Decision Diagrams (BDDs). In the model checking community, BDDs have been s...
Knowledge processing is very demanding on computer architectures. Knowledge processing generates subcomputation paths at an exponential rate. It is memory intensive and has high c...
This survey is concerned with the size of perfect formulations for combinatorial optimization problems. By "perfect formulation", we mean a system of linear inequalities...