On the Joint Entropy of dd-Wise-Independent Variables

preprint2016arXivOpen access

Abstract

How low can the joint entropy of nn dd-wise independent (for d≥2d\ge2) discrete random variables be, subject to given constraints on the individual distributions (say, no value may be taken by a variable with probability greater than pp, for p<1p<1)? This question has been posed and partially answered in a recent work of Babai. In this paper we improve some of his bounds, prove new bounds in a wider range of parameters and show matching upper bounds in some special cases. In particular, we prove tight lower bounds for the min-entropy (as well as the entropy) of pairwise and three-wise independent balanced binary variables for infinitely many values of nn.

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