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It is well known that the ratio of the number of clauses to the number of variables in a random k-SAT instance is highly correlated with the instance's empirical hardness. We consider the problem of identifying such features of random SAT instances automatically using machine learning. We describe and analyze models for three SAT solvers—kcnfs, oksolver and(More)
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