TY - GEN
T1 - Approximate Gács-Körner Common Information
AU - Salamatian, Salman
AU - Cohen, Asaf
AU - Medard, Muriel
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/6/1
Y1 - 2020/6/1
N2 - We propose to exploit the structure of the correlation between two random variables X and Y via a relaxation on the Common Information problem of Gács and Körner (GK Common Information). Consider two correlated sources X and Y generated from a joint distribution PX,Y. We study embeddings of X into discrete random variables U, such that H(U|Y) ≤ δ, while maximizing I(X; U). When δ = 0, this reduces to the GK Common Information problem. However, unlike the GK Common Information, which is known to be zero for many pairs of random variables (X, Y), we show that this relaxation allows to capture the structure in the correlation between X and Y for a much broader range of joint distributions, and showcase applications for some problems in multi-terminal information theory.
AB - We propose to exploit the structure of the correlation between two random variables X and Y via a relaxation on the Common Information problem of Gács and Körner (GK Common Information). Consider two correlated sources X and Y generated from a joint distribution PX,Y. We study embeddings of X into discrete random variables U, such that H(U|Y) ≤ δ, while maximizing I(X; U). When δ = 0, this reduces to the GK Common Information problem. However, unlike the GK Common Information, which is known to be zero for many pairs of random variables (X, Y), we show that this relaxation allows to capture the structure in the correlation between X and Y for a much broader range of joint distributions, and showcase applications for some problems in multi-terminal information theory.
UR - http://www.scopus.com/inward/record.url?scp=85090412585&partnerID=8YFLogxK
U2 - 10.1109/ISIT44484.2020.9173956
DO - 10.1109/ISIT44484.2020.9173956
M3 - Conference contribution
AN - SCOPUS:85090412585
T3 - IEEE International Symposium on Information Theory - Proceedings
SP - 2234
EP - 2239
BT - 2020 IEEE International Symposium on Information Theory, ISIT 2020 - Proceedings
PB - Institute of Electrical and Electronics Engineers
T2 - 2020 IEEE International Symposium on Information Theory, ISIT 2020
Y2 - 21 July 2020 through 26 July 2020
ER -