Near-Uniform Sampling of Combinatorial Spaces Using XOR Constraints

Gomes, Carla P., Sabharwal, Ashish, Selman, Bart

Neural Information Processing Systems 

We propose a new technique for sampling the solutions of combinatorial problems in a near-uniform manner. We focus on problems specified as a Boolean formula, i.e., on SAT instances. Sampling for SAT problems has been shown to have interesting connections with probabilistic reasoning, making practical sampling algorithms for SAT highly desirable. The best current approaches are based on Markov Chain Monte Carlo methods, which have some practical limitations.

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