Computational Complexity, volume 25, issue 1, pages 153-175
The complexity of estimating min-entropy
Thomas Watson
1
Publication type: Journal Article
Publication date: 2014-09-06
Journal:
Computational Complexity
scimago Q2
SJR: 0.453
CiteScore: 1.5
Impact factor: 0.7
ISSN: 10163328, 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).
Found
Are you a researcher?
Create a profile to get free access to personal recommendations for colleagues and new articles.