Abstract : Sharp exponential deviation estimates of the information content as well as a sharp bound on the varentropy are obtained for convex probability measures on Euclidean spaces. These provide, in a sense, a nonasymptotic equipartition property for convex measures even in the absence of stationarity-type assumptions.
https://hal-upec-upem.archives-ouvertes.fr/hal-01590229
Contributor : Matthieu Fradelizi <>
Submitted on : Tuesday, September 19, 2017 - 2:02:27 PM Last modification on : Tuesday, December 8, 2020 - 9:47:20 AM
Jiange Li, Matthieu Fradelizi, Mokshay Madiman. Information concentration for convex measures. 2016 IEEE International Symposium on Information Theory (ISIT 2016), Jul 2016, Barcelone, Spain. pp.1128-1132, ⟨10.1109/ISIT.2016.7541475⟩. ⟨hal-01590229⟩