Add to ORKGTwo alternative exact characterizations of the minimum error probability of Bayesian M-ary hypothesis testing are derived. The first expression corresponds to the error probability of an induced binary hypothesis test and implies the tightness of the meta-converse bound by Polyanskiy et al.; the second expression is a function of an information-spectrum measure and implies the tightness of a generalized Verdú-Han lower bound. The formulas characterize the minimum error probability of several problems in information theory and help to identify the steps where existing converse bounds are loose
We propose a saddlepoint approximation of the error probability of a binary hypothesis test between ...
We propose a saddlepoint approximation of the error probability of a binary hypothesis test between ...
Abstract—We show that the meta-converse bound derived by Polyanskiy et al. provides the exact error ...
Two alternative exact characterizations of the minimum error probability of Bayesian M-ary hypothesi...
Two alternative exact characterizations of the minimum error probability of Bayesian M-ary hypothesi...
Two alternative exact characterizations of the minimum error probability of Bayesian M-ary hypothesi...
Abstract—The inverse relation between mutual information (MI) and Bayesian error is sharpened by der...
In statistical inference problems, we wish to obtain lower bounds on the minimax risk, that is to b...
In statistical inference problems, we wish to obtain lower bounds on the minimax risk, that is to bo...
In statistical inference problems, we wish to obtain lower bounds on the minimax risk, that is to bo...
We propose a saddlepoint approximation of the error probability of a binary hypothesis test between ...
We propose a saddlepoint approximation of the error probability of a binary hypothesis test between ...
The testing of two-sided hypotheses in univariate and multivariate situations is considered. The goa...
The testing of two-sided hypotheses in univariate and multivariate situations is considered. The goa...
© 2016 IEEE. We revisit the problem of asymmetric binary hypothesis testing against a composite alte...
We propose a saddlepoint approximation of the error probability of a binary hypothesis test between ...
We propose a saddlepoint approximation of the error probability of a binary hypothesis test between ...
Abstract—We show that the meta-converse bound derived by Polyanskiy et al. provides the exact error ...
Two alternative exact characterizations of the minimum error probability of Bayesian M-ary hypothesi...
Two alternative exact characterizations of the minimum error probability of Bayesian M-ary hypothesi...
Two alternative exact characterizations of the minimum error probability of Bayesian M-ary hypothesi...
Abstract—The inverse relation between mutual information (MI) and Bayesian error is sharpened by der...
In statistical inference problems, we wish to obtain lower bounds on the minimax risk, that is to b...
In statistical inference problems, we wish to obtain lower bounds on the minimax risk, that is to bo...
In statistical inference problems, we wish to obtain lower bounds on the minimax risk, that is to bo...
We propose a saddlepoint approximation of the error probability of a binary hypothesis test between ...
We propose a saddlepoint approximation of the error probability of a binary hypothesis test between ...
The testing of two-sided hypotheses in univariate and multivariate situations is considered. The goa...
The testing of two-sided hypotheses in univariate and multivariate situations is considered. The goa...
© 2016 IEEE. We revisit the problem of asymmetric binary hypothesis testing against a composite alte...
We propose a saddlepoint approximation of the error probability of a binary hypothesis test between ...
We propose a saddlepoint approximation of the error probability of a binary hypothesis test between ...
Abstract—We show that the meta-converse bound derived by Polyanskiy et al. provides the exact error ...