@inproceedings{fc3ad338ec4d4b01a5246cc8dcee7981,
title = "Information concentration for convex measures",
abstract = "Sharp exponential deviation estimates for 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.",
keywords = "Varentropy, asymptotic equipartition, concentration, convex measure, log-concave",
author = "Jiange Li and Matthieu Fradelizi and Mokshay Madiman",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 IEEE International Symposium on Information Theory, ISIT 2016 ; Conference date: 10-07-2016 Through 15-07-2016",
year = "2016",
month = aug,
day = "10",
doi = "10.1109/ISIT.2016.7541475",
language = "英语",
series = "IEEE International Symposium on Information Theory - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1128--1132",
booktitle = "Proceedings - 2016 IEEE International Symposium on Information Theory, ISIT 2016",
address = "美国",
}