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37 votes
3 answers
3k views

An entropy inequality

Let $X,Y$ be probability measures on $\{1,2,\dots,n\}$, and set $K=\sum_i\sqrt{X(i)Y(i)}$ so that $Z:=\frac{1}{K}\sqrt{XY}$ is also a probability measure on $\{1,2,\dots,n\}$. How can we prove the ...
Eric Naslund's user avatar
  • 11.4k
18 votes
3 answers
3k views

Entropy and total variation distance

Let $X$, $Y$ be discrete random variables taking values within the same set of $N$ elements. Let the total variation distance $|P-Q|$ (which is half the $L_1$ distance between the distributions of $P$ ...
H A Helfgott's user avatar
  • 20.2k
15 votes
1 answer
703 views

Information inequalities

What are the feasible $2^n$-tuples of entropies $h(S) := H(X_{i_1},\dots,X_{i_{|S|}})$ where $X_1,\dots,X_n$ are discrete random variables with some (unknown) joint probability distribution as $S=\{...
James Propp's user avatar
  • 19.7k
13 votes
2 answers
1k views

Probability vector $p$ majorizes its normalized entropy vector $\small \frac{-p\log p}{H(p)}$

I guess the following inequality $$ \sum_{i=1}^n g \left (\frac{-p_i \log p_i}{H(\boldsymbol{p})} \right ) \le \sum_{i=1}^n g (p_i)$$ holds for any continuous convex function $g$ and any probability ...
Amir's user avatar
  • 303
11 votes
1 answer
676 views

Entropy arguments used by Jean Bourgain

My question comes from understanding a probabilistic inequality in Bourgain's paper on Erdős simiarilty problem: Construction of sets of positive measure not containing an affine image of a given ...
Tutukeainie's user avatar
10 votes
3 answers
803 views

Discrete entropy of the integer part of a random variable

Let $X$ be a real valued random variable. Of course, the integer part $\lfloor X \rfloor$ of $X$ is a discrete random variable taking values in $\mathbb{Z}$. We can therefore define its discrete ...
Goulifet's user avatar
  • 2,306
8 votes
1 answer
718 views

Relative Entropy and p-norm

I asked this question on StackExchange but could not get any answer, therefore, I am posting it here. I am currently reading the book "A Dynamical Approach to Random Matrix Theory". The ...
Raghav's user avatar
  • 371
6 votes
0 answers
342 views

Maximizing Renyi entropy for a certain channel

The channel under consideration is $T = A + B$, where $A$ and $B$ take on values in $\{0, 1\}$ according to a probability mass function. Let (joint) random vector $(A_1, A_2,\ldots, A_n)$ be denoted ...
gandalfthegreat's user avatar
3 votes
1 answer
205 views

Bound on an integral representing a difference of two relative entropies

Let $ f : [0,1] \to \mathbb{R} $ be a function satisfying: 1.) $ |f(x)| \leqslant a $ for some $ a < 1 $, and 2.) $ \int_0^1 f(x) {\mathrm d}x = 0 $. I would like to know whether the following ...
aleph's user avatar
  • 503
2 votes
0 answers
69 views

A distribution $\pi \propto \exp(-f)$ satisfies log-Sobolev inequality, does $\exp(-af)$ also satisfy LSI?

Assume a distribution $\pi \propto e^{-f}$ satisfies log-Sobolev inequality (LSI) $$\forall \rho \in P(\mathbb{R}^n), \quad KL(\rho\| \pi) \le \frac{1}{2\lambda} I(\rho \| \pi)$$ with LSI constant $\...
JIaojiao Fan's user avatar
0 votes
1 answer
147 views

Trying to prove an inequality (looks similar to entropy)

I'm trying to prove the following inequality (or something similar, up to a constant factor in either side of the inequality): $$k\cdot\sum_{i=1}^{k}x_{i}\cdot\ln\left(x_{i}\right)\geq\sum_{i=1}^{k}x_{...
danieljannai's user avatar
-1 votes
1 answer
159 views

Bounding difference of two mutual information with different distributions on random variables

Let $A$, $B$ and $C$ be three random variables and $p_{A,B,C}=p_Ap_Bp_{C|A,B}$ and $q_{A,B,C}=p_Aq_{B|A}p_{C|A,B}$ be two distributions on them. Then, we can conclude that? \begin{align*} \lvert I_p(A,...
Math_Y's user avatar
  • 287