Skip to Main content Skip to Navigation
Conference papers

Information concentration for convex measures

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.
Document type :
Conference papers
Complete list of metadata

Cited literature [15 references]  Display  Hide  Download

https://hal-upec-upem.archives-ouvertes.fr/hal-01590229
Contributor : Matthieu Fradelizi Connect in order to contact the contributor
Submitted on : Tuesday, September 19, 2017 - 2:02:27 PM
Last modification on : Wednesday, October 27, 2021 - 1:25:48 PM

File

FLM-isit16-final.pdf
Files produced by the author(s)

Identifiers

Collections

`

Citation

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⟩

Share

Metrics

Record views

454

Files downloads

1258