Goldreich, Sahai, and Vadhan (CRYPTO 1999) proved that the promise problem for esti-mating 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 2002).
We investigate the complexity of computing entropy of various Markovian models including Markov Chai...
We investigate the complexity of computing entropy of various Markovian models including Markov Chai...
Hidden Markov chains are widely applied statistical models of stochastic processes, from fundamental...
Goldreich et al. (CRYPTO 1999) proved that the promise problem for estimating the Shannon entropy of...
It was recently shown that estimating the Shannon entropy H(p) of a discrete k-symbol distribution p...
It was recently shown that estimating the Shannon entropy H(p) of a discrete k-symbol distribution p...
We consider the problem of approximating the entropy of a discrete distribution under several models...
Let X_1,..., X_n be a sequence of n classical random variables and consider a sample Xs_1,..., Xs_r ...
We consider the problems of deciding whether the joint distribution sampled by a given circuit has c...
International audienceThe channel capacity of a deterministic system with confidential data is an up...
We investigate the complexity of computing entropy of various Markovian models including Markov Cha...
It was recently shown that estimating the Shannon entropy H(p) of a discrete k-symbol distribution p...
Abstract. The channel capacity of a deterministic system with confidential data is an upper bound on...
We investigate the complexity of computing entropy of various Markovian models including Markov Chai...
We investigate the complexity of computing entropy of various Markovian models including Markov Chai...
Hidden Markov chains are widely applied statistical models of stochastic processes, from fundamental...
Goldreich et al. (CRYPTO 1999) proved that the promise problem for estimating the Shannon entropy of...
It was recently shown that estimating the Shannon entropy H(p) of a discrete k-symbol distribution p...
It was recently shown that estimating the Shannon entropy H(p) of a discrete k-symbol distribution p...
We consider the problem of approximating the entropy of a discrete distribution under several models...
Let X_1,..., X_n be a sequence of n classical random variables and consider a sample Xs_1,..., Xs_r ...
We consider the problems of deciding whether the joint distribution sampled by a given circuit has c...
International audienceThe channel capacity of a deterministic system with confidential data is an up...
We investigate the complexity of computing entropy of various Markovian models including Markov Cha...
It was recently shown that estimating the Shannon entropy H(p) of a discrete k-symbol distribution p...
Abstract. The channel capacity of a deterministic system with confidential data is an upper bound on...
We investigate the complexity of computing entropy of various Markovian models including Markov Chai...
We investigate the complexity of computing entropy of various Markovian models including Markov Chai...
Hidden Markov chains are widely applied statistical models of stochastic processes, from fundamental...