We propose a novel a framework for deriving approximations for intractable probabilistic models. This framework is based on a free energy (negative log marginal likelihood) and ca...
This paper introduces a new CNF encoding of pseudo-Boolean constraints, which allows unit propagation to maintain generalized arc consistency. In the worst case, the size of the p...
It is known that a tree convex network is globally consistent if it is path consistent. However, if a tree convex network is not path consistent, enforcing path consistency on it ...
Probabilistic language models are critical to applications in natural language processing that include speech recognition, optical character recognition, and interfaces for text e...
We first define a mapping from CSP to many-valued SAT which allows to solve CSP instances with many-valued SAT solvers. Second, we define a new many-valued resolution rule and p...