2020 IEEE International Symposium
on Information Theory
21-26 June 2020 • Los Angeles, California, USA
| Paper ID | S.10.3 | ||
| Paper Title | Usable deviation bounds for the information content of convex measures | ||
| Authors | Matthieu Fradelizi, Université Paris-Est, France; Jiange Li, Mokshay Madiman, University of Delaware, United States | ||
| Session | S.10: Information Measures II | ||
| Presentation | Lecture | ||
| Track | Shannon Theory | ||
| Manuscript | Click here to download the manuscript | ||
| Virtual Presentation | Click here to watch in the Virtual Symposium | ||
| Abstract | Usable upper and lower deviation bounds are given for the information content of random vectors from a $s$-concave probability density function. Some information-theoretic interpretation, related to non-asymptotic equipartition properties, is also developed. | ||
Plan Ahead
2021 IEEE International Symposium on Information Theory
11-16 July 2021 | Melbourne, Victoria, Australia
