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Sharp indistinguishability bounds from non-uniform approximations
[article]
2021
arXiv
pre-print
We study the problem of distinguishing between two symmetric probability distributions over n bits by observing k bits of a sample, subject to the constraint that all k-1-wise marginal distributions of the two distributions are identical to each other. Previous works of Bogdanov et al. and of Huang and Viola have established approximately tight results on the maximal statistical distance when k is at most a small constant fraction of n and Naor and Shamir gave a tight bound for all k in the
arXiv:2103.07842v1
fatcat:rvxlox6i3rcjvfcdg55z5m5koy