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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
5 votes
2 answers
245 views

Differentiability of the map $x\mapsto \delta_x$ in the Arens-Eells/Lipschitz-free space

$\DeclareMathOperator\AE{AE}\DeclareMathOperator\Lip{Lip}$Let $\AE(X)$ denote the Arens-Eells space on a Banach space $X$. Consider the map: $$ \begin{aligned} \delta: X & \rightarrow \AE(X) \\ x&...
AngeloPiadetta's user avatar
3 votes
1 answer
350 views

Talagrand's inequality for L1 norm

I have a series of $n$ independent random variables $X_1,\ldots, X_n$, each with the support $[0,1]$, and a monotone convex function $f:\mathbb{R}^n \rightarrow \mathbb{R}$ that is 1-Lipshitz in L1 ...
Tomer Ezra's user avatar
5 votes
0 answers
74 views

Concentration bound on additive functions with constraints

Given a family of sets $F \subseteq P(\{1,\ldots,n\})$. I define the function $f_F:[0,1]^n \rightarrow R$ to be $f_F(x_1,\ldots,x_n)= \max_{S \in F} \sum_{j \in S} x_j$. Given a series of independent ...
Tomer Ezra's user avatar
8 votes
2 answers
1k views

Talagrand's inequality for the discrete cube

Talagrand showed that if $f$ is a convex $1$-Lipschitz function on $\mathbb{R}^n$, and if $\mu$ is a product of probability measures supported over the interval, then $f$ has Gaussian concentration w....
alesia's user avatar
  • 2,772
21 votes
2 answers
3k views

A measure on the space of probability measures

This question was originaly posted in the stackexchange https://math.stackexchange.com/questions/1226701/a-measure-on-the-space-of-probability-measures but since it only got a comment I decided to ...
Bruce Wayne's user avatar
26 votes
3 answers
11k views

L1 distance between gaussian measures

L1 distance between gaussian measures: Definition Let $P_1$ and $P_0$ be two gaussian measures on $\mathbb{R}^p$ with respective "mean,Variance" $m_1,C_1$ and $m_0,C_0$ (I assume matrices have full ...
robin girard's user avatar
7 votes
2 answers
460 views

Gaussian Surface Area of Positive Semidefinite Cone

Let $\mathbb{R}^n$ be the Euclidean space and $A \subseteq \mathbb{R}^n$ be a sufficiently regular set, e.g., one that has smooth boundary or is convex. We define the $\epsilon$-neighbor of $A$ in the ...
Minkov's user avatar
  • 1,127
4 votes
1 answer
193 views

A bound on the square distance of a random walk on undirected graph

Fact: Let $G$ be an $n$-vertex undirected graph and $(X_s)_{s\in \mathbb N}$ a stationary random walk on $G$. Then for every $s\in \mathbb{N}$, $ \mathbb{E}[d_G(X_s,X_0)^2] \le C s \log n $, for some ...
Manor Mendel's user avatar
6 votes
0 answers
281 views

Covariance operator analogue for manifolds and respective measure manifolds

Assume $E$ is a connected riemannian manifold with geodesic metric space structure given by $d$ and $P$ is a probability measure over $E$ with Borel sigma-algebra given by this metric structure. Also ...
Nik Bren's user avatar
  • 519
2 votes
0 answers
60 views

Mean width of intersection of two elipsoid

My question is regarding mean widths. For a set $\mathcal{T}$ define the mean width \begin{align*} \omega(T)=\mathbb{E}_{\mathbf{g}\sim\mathcal{N}(0,\mathbf{I})}\bigg[\underset{\mathbf{u}\in\mathcal{...
Anahita's user avatar
  • 363
6 votes
1 answer
396 views

Does a metric refine the weak-* topology on a dual space?

Let $X$ be a topological affine space over $\mathbb C$, with no additional assumptions. Let $X^*$ denote its dual space of continuous affine functionals $X \to \mathbb C$, equipped with the weak-$*$ ...
Tom LaGatta's user avatar
  • 8,512
9 votes
2 answers
674 views

Small crown probabilities (and infinite dimensional margin assumption)

My question is: How do I find sharp upper bounds on $P(|q|\leq \epsilon)$ uniformly over a set of gaussian polynomes $q$ of degree two. Notations and definitions (to make the question rigorous) Let ...
11 votes
0 answers
601 views

High-dimensional geometry: Top-down Vs. Bottom-up

There are several ways to leverage one's intuition from low-dimensional geometry to understand high-dimensional phenomena. For example, one can get a clearer picture of the behaviour of high-...
Simon Lyons's user avatar
  • 1,666