Exploiting partial knowledge of satisfying assignments
نویسندگان
چکیده
منابع مشابه
Learning from satisfying assignments
This paper studies the problem of learning “low-complexity” probability distributions over the Boolean hypercube {−1, 1}. As in the standard PAC learning model, a learning problem in our framework is defined by a class C of Boolean functions over {−1, 1}, but in our model the learning algorithm is given uniform random satisfying assignments of an unknown f ∈ C and its goal is to output a highac...
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Suppose there is a bag containing red balls and blue balls. You would like to estimate the fraction of red balls in the bag. However, you are only allowed to sample randomly from the bag with replacement. The straightforward method is to make T random samples and use the fraction of red balls in the random samples as an estimate of the true fraction. The question is: how many samples are enough...
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A minimum satisfying assignment of a formula is a minimumcost partial assignment of values to the variables in the formula that guarantees the formula is true. Minimum satisfying assignments have applications in software and hardware verification, electronic design automation, and diagnostic and abductive reasoning. While the problem of computing minimum satisfying assignments has been widely s...
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ژورنال
عنوان ژورنال: Discrete Applied Mathematics
سال: 2007
ISSN: 0166-218X
DOI: 10.1016/j.dam.2005.10.019