To model combinatorial decision problems involving uncertainty and probability, we extend the stochastic constraint programming framework proposed in [Walsh, 2002] along a number ...
We address the problem of finding the most likely assignment or MAP estimation in a Markov random field. We analyze the linear programming formulation of MAP through the lens of...
The paper presents a compiler framework for analyzing and optimizing OpenMP programs. The framework includes Parallel Control Flow Graph and Parallel Data Flow equations based on t...
We consider the problem of updating nonmonotonic knowledge bases represented by epistemic logic programs where disjunctive information and notions of knowledge and beliefs can be ...
Our experience in the IDAS natural language generation project has shown us that IDAS'S KLONE-like classifier, originally built solely to hold a domain knowledge base, could ...