May  2007, 1(2): 239-242. doi: 10.3934/amc.2007.1.239

The final form of Tao's inequality relating conditional expectation and conditional mutual information

1. 

Department of Mathematics, University of Bielefeld, POB 100131, D-33501 Bielefeld, Germany

Received  December 2006 Published  April 2007

Recently Terence Tao approached Szemerédi's Regularity Lemma from the perspectives of Probability Theory and of Information Theory instead of Graph Theory and found a stronger variant of this lemma, which involves a new parameter. To pass from an entropy formulation to an expectation formulation he found the following: Let $Y$ , and $X,X'$ be discrete random variables taking values in $mathcal Y$ and $mathcal X$, respectively, where $mathcal Y \subset$ [ −1, 1 ], and with $X' = f(X)$ for a (deterministic) function $f$. Then we have
     $ \E(|\E(Y|X')-\E(Y|X)|)\leq2I(X\wedge Y|X')^{\frac12}.$
We show that the constant $2$ can be improved to $(2 \l n2)^{\frac{1}{2}}$ and that this is the best possible constant.
Citation: Rudolf Ahlswede. The final form of Tao's inequality relating conditional expectation and conditional mutual information. Advances in Mathematics of Communications, 2007, 1 (2) : 239-242. doi: 10.3934/amc.2007.1.239
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