conference paper
Achievability of nearly-exact alignment for correlated Gaussian databases
2020
2020 IEEE International Symposium on Information Theory (ISIT)
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.
Type
conference paper
Web of Science ID
WOS:000714963401052
Author(s)
Date Issued
2020
Publisher
Publisher place
New York
Published in
2020 IEEE International Symposium on Information Theory (ISIT)
ISBN of the book
978-1-7281-6432-8
Series title/Series vol.
IEEE International Symposium on Information Theory
Start page
1230
End page
1235
Editorial or Peer reviewed
REVIEWED
Written at
EPFL
EPFL units
| Event name | Event place | Event date |
Los Angeles, CA, USA, Virtual Conference | June 21-26, 2020 | |
Use this identifier to reference this record