Computational Complexity, volume 25, issue 1, pages 153-175

The complexity of estimating min-entropy

Publication typeJournal Article
Publication date2014-09-06
scimago Q2
SJR0.453
CiteScore1.5
Impact factor0.7
ISSN10163328, 14208954
General Mathematics
Computational Mathematics
Computational Theory and Mathematics
Theoretical Computer Science
Abstract
Goldreich et al. (CRYPTO 1999) proved that the promise problem for estimating the Shannon entropy of a distribution sampled by a given circuit is NISZK-complete. We consider the analogous problem for estimating the min-entropy and prove that it is SBP-complete, where SBP is the class of promise problems that correspond to approximate counting of NP witnesses. The result holds even when the sampling circuits are restricted to be 3-local. For logarithmic-space samplers, we observe that this problem is NP-complete by a result of Lyngsø and Pedersen on hidden Markov models (JCSS 65(3):545–569, 2002).
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