A new paper from the group has been accepted for publication

The paper “Bayesian M-ary Hypothesis Testing: The Meta-Converse and Verdú-Han Bounds are Tight” by G. Vazquez-Vilar, A. Tauste Campo, A. Guillén i Fàbregas and A. Martinez has been accepted for publication in IEEE Transactions on Information Theory.

Two 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.