Skip to main content
Search type Search syntax
Tags [tag]
Exact "words here"
Author user:1234
user:me (yours)
Score score:3 (3+)
score:0 (none)
Answers answers:3 (3+)
answers:0 (none)
isaccepted:yes
hasaccepted:no
inquestion:1234
Views views:250
Code code:"if (foo != bar)"
Sections title:apples
body:"apples oranges"
URL url:"*.example.com"
Saves in:saves
Status closed:yes
duplicate:no
migrated:no
wiki:no
Types is:question
is:answer
Exclude -[tag]
-apples
For more details on advanced search visit our help page
Results tagged with
Search options not deleted user 1044

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.

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
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
  • 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
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
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 …
Mark Meckes's user avatar
  • 11.4k