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Theoretical and experimental aspects of information theory and coding theory. This tag covers but is not limited to following branches: information theory, information geometry, optimal transportation theory, coding theory.

6 votes
Accepted

distance in terms of the variance between two absolutely continuous probability measures

The Kullback-Leibler divergence is a special case of Rényi divergence. In your notation, for $\alpha > 0$, the Rényi divergence of order $\alpha$ is defined by $$ D_\alpha(p_0,p_1) = \frac{1}{\alpha …
The Amplitwist's user avatar
1 vote

Convergence of an empirical distribution w.r.t. the Hellinger distance

Here's a quick argument to get something in the direction of what you want, but rather weaker than you asked for. First of all, using the Cauchy-Schwarz inequality, $$ \mathbb{E} d_H(P,\hat{P}_n) \le …
Mark Meckes's user avatar
  • 11.4k
7 votes

Entropy of a general prob. measure

It is not. If a probability measure on $\mathbb{R}$ is absolutely continuous and has density $f$, then "entropy" usually refers to the differential entropy, defined in the Wikipedia page falagar link …
Mark Meckes's user avatar
  • 11.4k
1 vote

l^p space inequality related to compressed sensing

Regarding the last part of the question, I haven't looked at either of the following books myself, but I've seen them referred to for systematic presentations of the theory of quasinormed spaces (whic …
Mark Meckes's user avatar
  • 11.4k
5 votes

When are probability distributions completely determined by their moments?

I don't have it on hand, but Billingsley's book "Probability and Measure" has a nice section on this issue, including the classic example of a distribution not uniquely determined by its moments: the …
Mark Meckes's user avatar
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