@inproceedings{559eaf453ecd48e29ff7fdc34b8cc0af,
title = "Achievability of nearly-exact alignment for correlated Gaussian databases",
abstract = "We study the conditions that allow for the alignment of correlated databases with multivariate Gaussian features. We present some analysis tools that allow us to go beyond the achievability result for exact alignment and derive the condition for nearly-exact alignment. Our main theorem gives an expression for the order of magnitude of the error in alignment as a function of mutual information between features.",
author = "Dai, {Osman Emre} and Daniel Cullina and Negar Kiyavash",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 2020 IEEE International Symposium on Information Theory, ISIT 2020 ; Conference date: 21-07-2020 Through 26-07-2020",
year = "2020",
month = jun,
doi = "10.1109/ISIT44484.2020.9174507",
language = "English (US)",
series = "IEEE International Symposium on Information Theory - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1230--1235",
booktitle = "2020 IEEE International Symposium on Information Theory, ISIT 2020 - Proceedings",
address = "United States",
}