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40 votes
5 answers
5k views

"Entropy" proof of Brunn-Minkowski Inequality?

I read in an information theory textbook the Brunn-Minkowski inequality follows from the Entropy Power inequality. The first one says that if $A,B$ are convex polygons in $\mathbb{R}^d$, then $$ m(...
john mangual's user avatar
  • 22.8k
11 votes
1 answer
320 views

Conceptual explanation for the appearance of entropy in $\frac{d}{dp}\|x\|_p$

For $x\in \mathbb{R}^d$, an elementary computation yields that $$\frac{d}{dp}\log \|x\|_p =\frac{1}{p^2}\sum_{i=1}^d \frac{|x_i|^p}{\|x\|_p^p}\log \frac{|x_i|^p}{\|x\|_p^p}=-\frac{1}{p^2}\operatorname{...
tmh's user avatar
  • 775
9 votes
1 answer
385 views

A Generalized Version of Maximal Correlation and Hypercontractivity of Conditional Expectation Operator

Given a pair of random variables $(X,Y)$ over a product space $\mathcal{X}\times \mathcal{Y}$, the maximal correlation coefficient is defined as $$\rho_2(X;Y):=\sup\frac{\mathbb{E}[f(X)g(Y)]}{||f||_2||...
math-Student's user avatar
  • 1,109
8 votes
2 answers
540 views

Maximum entropy priors in infinite dimensional spaces

Is there an extension of maximum entropy probability distributions for function spaces? For $\mathbb{R}^n$ and discrete spaces, there is much literature about this problem under names such as "non-...
Nick Alger's user avatar
  • 1,160
5 votes
2 answers
631 views

Proving that a complicated function is eventually concave

I have a function $f:\mathbb{R}^+ \to \mathbb{R}^+$ that I want to prove is eventually concave - i.e. that there exists $\gamma _0 > 0$ such that for every $\gamma>\gamma_0$, $f(\gamma)$ is ...
Yair Carmon's user avatar
5 votes
1 answer
450 views

Brascamp-Lieb inequalities on the sphere

In the paper [CLL], Carlen, Lieb, and Loss demonstrate a version of the Young inequality on the sphere $S^{N-1}$ in $\mathbb{R}^N$. For positive functions $f_j$ on $[-1,1]$, the following bound holds:...
felipeh's user avatar
  • 452
5 votes
1 answer
666 views

Question regarding divergence

Let $E$ be a closed and convex set of distributions on a finite set $A$. Let $P',Q'\notin E$ and let $P^{\star},Q^{\star}$ be their respective estimates in $E$ with respect to the KL-divergence, i.e.,...
Ashok's user avatar
  • 779
4 votes
1 answer
638 views

Stability in algebraic geometry

Suppose I have a collection of polynomials with multiple variables (more polynomials than variables, say), and I'm given noisy versions the values of these polynomials at a certain unknown point. I ...
Dustin G. Mixon's user avatar
1 vote
1 answer
182 views

Inequalities involving entropy: quantum discord and mutual information

My question is inspired by the following paper of Olivier and Żurek but for this question to be self-contained I will recall all the necessary definitions: for a quantum state $\rho$ we define the ...
truebaran's user avatar
  • 9,330
1 vote
0 answers
45 views

Existence of optimal entropic weights for empirical modeling

Let $\mathcal{X} = [0,1]^n$ be the input space and $\mathcal{Y} = \{1, ..., n_c\}$ be a discrete output space. Let $D = \{(x_i, y_i)\}_{i=1}^N \subset \mathcal{X} \times \mathcal{Y}$ be a training ...
Damien's user avatar
  • 111
1 vote
0 answers
65 views

Normalizing constants preserve metric entropy

Suppose $\mathcal{F}=\left\{f\in L^2([a,b]): 0<\underline{c}\leq f\leq\overline{c} \right\}$. Consider the following transformation $$\tilde{\mathcal{F}} := \left\{\frac{f}{\int f d\mu}: f\in \...
lucaszz's user avatar
  • 11
0 votes
1 answer
158 views

Encoding numbers with relationship into one and back

Given a set of many variables $S=\{x_1,x_2, ...., x_i\}$, and any subset $S'$ of $S$, I need a function $f$ which maps $S'$ to a value $x$ and a function $f'$ which maps $x$ back to set $S'$. I know ...
Rise of Kingdom's user avatar