Abstract
We consider approximations of probability distributions over ℤ n p . We present an approach to estimate the quality of approximations towards the construction of small probability spaces which are used to derandomize algorithms. In contrast to results by Even et al. [13], our methods are simple, and for reasonably small p, we get smaller sample spaces. Our considerations are motivated by a problem which was mentioned in recent work of Azar et al. [5], namely, how to construct in time polynomial in n a good approximation to the joint probability distribution of i.i.d. random variables X 1,...,X n where each X i has values in {0,1}. Our considerations improve on results in [5].
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© 1997 Springer-Verlag Berlin Heidelberg
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Bertram-Kretzberg, C., Lefmann, H. (1997). MODp-tests, almost independence and small probability spaces. In: Reischuk, R., Morvan, M. (eds) STACS 97. STACS 1997. Lecture Notes in Computer Science, vol 1200. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0023455
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DOI: https://doi.org/10.1007/BFb0023455
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