# Theory of Computing Seminar

Thursday
September 29, 2016
1:30 PM

**The entropy power inequality for the Renyi entropy **

**Speaker:**Arnaud Marsiglietti, Caltech

**Location:**Annenberg 213

**Abstract:**

The entropy power inequality, fundamental in Information Theory, states that for every independent continuous random vector X,Y in R^n$, one has N(X+Y) \geq N(X) + N(Y). Here N(X) denotes the entropy power of X, defined as N(X) = e^{2h(X)/n}, where h(X) is the entropy of X.

In this talk, we will see that the entropy power inequality can be extended to the Renyi entropy.

(based on a joint work with S. Bobkov)

In this talk, we will see that the entropy power inequality can be extended to the Renyi entropy.

(based on a joint work with S. Bobkov)

**Series**Theory of Computing Seminar Series

**Contact:** Thomas Vidick vidick@cms.caltech.edu