Abstract. A class of probabilistic-logic models is considered, which increases the expressibility from HMM's and SCFG's regular and contextfree languages to, in principle...
Abstract. We present a new technique called Monotonic Partial Order Reduction (MPOR) that effectively combines dynamic partial order reduction with symbolic state space exploration...
Abstract—Network flow models serve as a popular mathematical framework for the analysis and optimization of Multi-hop Wireless Networks. They also serve to provide the understan...
Abstract. Solutions to non-linear least squares problems play an essential role in structure and motion problems in computer vision. The predominant approach for solving these prob...
Abstract In recent years, the Constraint Programming (CP) and Operations Research (OR) communities have explored the advantages of combining CP and OR techniques to formulate and s...