@inproceedings{9a48b18201cf47a782497f7b887646c1,
title = "Infinity-R{\'e}nyi entropy power inequalities",
abstract = "An optimal ∞-R{\'e}nyi entropy power inequality is derived for d-dimensional random vectors. In fact, the authors establish a matrix ∞-EPI analogous to the generalization of the classical EPI established by Zamir and Feder. The result is achieved by demonstrating uniform distributions as extremizers of a certain class of ∞-R{\'e}nyi entropy inequalities, and then putting forth a new rearrangement inequality for the ∞-R{\'e}nyi entropy. Quantitative results are then derived as consequences of a new geometric inequality for uniform distributions on Euclidean balls.",
keywords = "Infinity entropy power inequality, Information measures, Max density, Renyi entropy",
author = "Peng Xu and James Melbourne and Mokshay Madiman",
year = "2017",
month = aug,
day = "9",
doi = "10.1109/ISIT.2017.8007077",
language = "English (US)",
series = "IEEE International Symposium on Information Theory - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "2985--2989",
booktitle = "2017 IEEE International Symposium on Information Theory, ISIT 2017",
note = "2017 IEEE International Symposium on Information Theory, ISIT 2017 ; Conference date: 25-06-2017 Through 30-06-2017",
}