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Logic and Probability: The Computational Connection

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I will discuss in this talk the subject of knowledge compilation of propositional knowledge bases and how it can form the basis for building state-of-the-art probabilistic reasoning systems. In the first part of the talk, I will focus on exact probabilistic reasoning and how it can be reduced to knowledge compilation, leading to an award-winning system for exact inference in the presence of local structure (determinism and context specific independence). In the second part of the talk, I will focus on approximate inference, and how it can be formulated in terms of “relaxing” logical constraints (equalities in particular) for the purpose of aiding the process of knowledge compilation. The resulting formulation, known as “Relax, Compensate and then Recover,” subsumes loopy belief propagation and some of its generalizations, and is the basis for an award-winning system at the UAI inference competition in 2010. I will also review in the talk some recent advances and ongoing work in the world of knowledge compilation and the impact it has on the state-of-the-art in probabilistic and symbolic reasoning.

This talk is part of the Microsoft Research Cambridge, public talks series.

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