@inproceedings{63a38e1aa9c44d73a4cba2ab8e5e90cf,
title = "Binary Maximal Correlation Bounds and Isoperimetric Inequalities via Anti-Concentration",
abstract = "This paper establishes a dimension-independent upper bound on the maximal correlation between Boolean functions of dependent random variables, in terms of the second and third singular values in their spectral decomposition, and the anti-concentration properties of the second singular vectors. This result has notable consequences, among which are: A strengthening of Witsenhausen's lower bound on the probability of disagreement between Boolean functions; a Poincar{\'e} inequality for bounded-cardinality functions; and improved lower bounds on the isoperimetric constant of Markov chains.",
author = "Dror Drach and Or Ordentlich and Ofer Shayevitz",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 2021 IEEE International Symposium on Information Theory, ISIT 2021 ; Conference date: 12-07-2021 Through 20-07-2021",
year = "2021",
month = jul,
day = "12",
doi = "https://doi.org/10.1109/ISIT45174.2021.9517829",
language = "الإنجليزيّة",
series = "IEEE International Symposium on Information Theory - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1284--1289",
booktitle = "2021 IEEE International Symposium on Information Theory, ISIT 2021 - Proceedings",
address = "الولايات المتّحدة",
}