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Questions tagged [measure-concentration]

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Lower bound on misclassification rate of Lipschitz functions in terms of Lipschitz constant

Important note @MateuszKwaśnicki in the comment section has raised a fundamental issue with the current statement of the problem. I'm trying to bugfix it. Setup I wish to show that a Lipschitz ...
dohmatob's user avatar
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1k views

Upper-bound KL divergence between sub-gaussian variables with same variance

A random variable $X$ is said to be sub-gaussian with mean $\mu$ and pseudo-variance $\sigma^2$ iff $$\mathbb \log(E[\exp(t(X-\mu))]) \le \frac{t^2}{2\sigma^2},\;\forall t \in \mathbb R. $$ It's a ...
dohmatob's user avatar
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4 votes
0 answers
162 views

Are sums extremal for subgaussian concentration?

Bobkov and Houdre https://projecteuclid.org/euclid.bj/1178291721 showed that among all $f:R^n\to R$ that are $1$-Lipschitz with respect to the $\ell_1$ metric, the variance is maximized by sums. ...
Aryeh Kontorovich's user avatar
3 votes
1 answer
305 views

Concentration of measure in graph theory

I am looking for elementary statements in graph theory that illustrate the concentration of measure phenomenon. (Say, something bit more interesting than most of graphs have diameter 2.)
Anton Petrunin's user avatar
10 votes
2 answers
455 views

Largest deviations for uniform order statistics

Let $n >0$. Let $X_1,\ldots,X_n$ be i.i.d. uniform random variable on $[0,1].$ Denote by $X^{(1)}\leq X^{(2)} \leq \cdots \leq X^{(n)}$ their order statistics, and write $\Delta^{(i)} = \vert X^{(...
Gericault's user avatar
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2 votes
1 answer
326 views

What is the Wiener measure of the curves with Hölder index $\frac 1 2$?

One may show that the Wiener measure (for curves in $\mathbb R^n$) is concentrated on the Hölder-continuous curves of Hölder index $< \frac 1 2$. What happens to the curves of Hölder index ...
Alex M.'s user avatar
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5 votes
1 answer
299 views

Variance modulo 1

The fact that the variance of the sum of independent random variables is the sum of their variances allows one to have a good understanding of how well-concentrated each term $X_i$ in a sum of $n$ ...
Jakub Konieczny's user avatar
3 votes
1 answer
294 views

Concentration inequalities specialized for log-likelihood / log-density functions

Let $P$ be a probability measure and $f$ be some probability density function (not necessarily related to $P$). Consider the function $$ L(X_1,\ldots,X_n) =\frac1n\sum_{i=1}^n\log f(X_i), \quad X_i\...
JohnA's user avatar
  • 710
1 vote
0 answers
34 views

Limiting law of quadratic functions of sample averages

Let $X_1,\cdots,X_n$ be independent centered univariate random variables. Let also $\{w_{ij}\}_{i,j=1}^{k,n}$ be a set of deterministic scalar weights, where $k\ll n$. Define sample averages $$ \...
Yining Wang's user avatar
-1 votes
2 answers
614 views

Bounded difference functions and sub-Gaussian random variables

We have the following standard theorem : Let $X$ be some set and $g : X^n \rightarrow \mathbb{R}$ be a measurable function such that it satisfies the ``bounded difference property" i.e $\exists$ $\{...
gradstudent's user avatar
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4 votes
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On symmetry and measure concentration rate for convex bodies

The concentration of measure on the cube $ [0, 1]^n $ equipped with uniform probability measure $\mu_{\infty}$, states that for any $A \subset [0, 1]^n $ with $ \mu_{\infty}(A) \geq \frac{1}{2} $, we ...
random_shape's user avatar
1 vote
0 answers
676 views

Are Outer Products of Sub-Gaussian Vectors Sub-Exponential?

$\newcommand\xx{\mathbf{x}}\newcommand\yy{\mathbf{y}}\newcommand\A{\mathbf{A}}\newcommand\aalpha{\boldsymbol{\alpha}}\newcommand\bbeta{\boldsymbol{\beta}}\newcommand\E{\mathbb{E}}\newcommand\inner[1]{\...
Conner DiPaolo's user avatar
4 votes
1 answer
290 views

On the 1/2 assumption on concentration of measure for continuous cube

The concentration of measure on $ [0, 1]^n $ equipped with uniform probability measure $\mu_{\infty}$, states that for any $A \subset [0, 1]^n $ with $ \mu_{\infty}(A) \geq \frac{1}{2} $, we have: $$...
random_shape's user avatar
4 votes
1 answer
1k views

Does variants of Bernstein and Freedman concentration inequalities exist with NO uniform bound on the range of RV or martingale differences

A classic formulation of the Bernstein inequality (from Wikipedia) is as follow: Let $X_1, \ldots, X_n$ be independent zero-mean random variables. Suppose that $|X_i|\leq M$ almost surely, for all $i$...
Jean Claude's user avatar
2 votes
1 answer
167 views

Concentration of emperical conditional probability

Assume sequence $(X_1,X_2, X_3, \ldots)$ is a first-order Markov sequence of real random variables where $X_i \in \mathcal{X}$ for some alphabet $\mathcal{X}$ of finite size $k$. Define emperical ...
Robert's user avatar
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7 votes
1 answer
466 views

Martingale version of Bernstein-type inequality for (slightly) heavy-tailed distributions?

It is known that for sub-exponentially distributed martingale difference sequence, the following Bernstein-type inequality holds: $$ ℙ\left(\left| \sum_{i=1}^N a_i X_i \right| \ge t \right) \le 2\...
Nikolayevich's user avatar
0 votes
0 answers
111 views

Capacity and measure

Fix $p\in [1, 2)$ and denote the $p$-capacity of a compact set $K$ as $p$-$\text{cap}(K)$, i.e., \begin{equation} p\text{-cap}(K)\equiv\left\{\int_{\mathbb{R}^2}|D\varphi|^p\ \mathrm{d}x\ \Big|\ \...
Nirav's user avatar
  • 347
5 votes
0 answers
543 views

Vector martingale concentration

Let $\varepsilon_1, \dots, \varepsilon_N$ be a martingale difference sequence in $R^d$ with $\|\varepsilon_n\| \le B_n, a.s.$ for each $n=1,\dots,N$. Do we have some Azuma-type concentration ...
Nikolayevich's user avatar
3 votes
2 answers
733 views

Concentration inequality for sum of iid random variables that involve KL distance

Conider $X \in \mathbb{R}^d$ and $Y \in \{0,1\}$, and a joint distribution $p_{XY}(x,y)$, and a set of $N$ i.i.d. samples $\{(X_i,Y_i)\}_{i=1}^{N}$. Define $p_{X0} = p_{XY}(x,0)$ and $p_{X1} = p_{XY}(...
Jeff's user avatar
  • 482
4 votes
1 answer
229 views

Product of estimates of mean values - Concentration of measure inequality

Let $X_{1},...,X_{d} \in \{-1,1\}^d$ be random variables, with $E[X_j]=\mu_j$. Having $n$ i.i.d. samples $x^{(i)}_1,x^{(i)}_2,....,x^{(i)}_d$, $i=1,...,n $, let $\hat{\mu}_{j}=\frac{1}{n}\sum^{n}_{i=1}...
user_Lee's user avatar
  • 107
3 votes
1 answer
196 views

Uniform Convergence for Vectors

$\textbf{Problem statement:}$ Let $\mathcal H:\mathcal X \rightarrow \{0,1\}$ be a class of Boolean functions for $\mathcal X \subset \mathbb R^n$, and let the VC Dimension of $\mathcal H$ be $VC_{...
AvidLearner's user avatar
7 votes
1 answer
976 views

Prove an anti-concentration inequality for a martingale

My problem can be described easily: I have a sequence $(X_l)_{l \in \mathbb{N}}$ of r.v. adapted to some filtration $(\mathcal{F}_l)_{l \in \mathbb{N}}$, such that $\left|X_{l+1}-X_l\right|\le R$ a. ...
T.T's user avatar
  • 73
1 vote
0 answers
376 views

Anti-concentration bounds for folded normal and inverse of gaussian variables

Are there any easy to use bounds on sums of the following kind : $$ \sum_{i = 1}^{i = N} |a_i| \geq P \\ a_i \sim \mathcal{N}(0, 1) \\ $$ and also for sums of the form : $$ \sum_{i = 1}^{i = M} \...
Govind Gopakumar's user avatar
1 vote
1 answer
249 views

On concentration of a sum random variable

Take a random variable defined as $$r=u_{11}v_{1}v_{1}+u_{12}v_{1}v_{2}+\dots+u_{n,n-1}v_{n}v_{n-1}+u_{nn}v_{n}v_{n}$$ where $v_{i}$ are independent uniform random variables from $\{0,\dots,b\}$, $u_{...
Turbo's user avatar
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3 votes
0 answers
77 views

A concentration problem of product of matrices

Let $A$ be an $n \times m$ matrix with non-negative entries and $B \in \mathbb{R^{n\times n}_{\geq 0}}, C \in \mathbb{R^{m\times m}_{\geq 0}}$ be random matrices where B and C are both symmetric and ...
ie86's user avatar
  • 195
2 votes
0 answers
323 views

McDiarmid's Inequality bounding deviation with multiplicative error?

Fix $m$ arbitrary values $x_1, x_2, ..., x_m$ in $[0,1]$, and an integer $n$. Obtain $n$-set $S$ by drawing $n \le m$ times randomly without replacement from $\{1,2,..,m\}$. Define r.v. $X = \sum_{i ...
Neal Young's user avatar
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
5 votes
0 answers
143 views

Is there a concentration inequality depending on dimension for a symmetric function on product space?

I recently read an elegant paper of Bobkov Bobkov, S.G., On concentration of measure on the cube, J. Math. Sci., New York 165, No. 1, 60-70 (2010); translation from Probl. Mat. Anal. 44, 55-64 (2010)....
Jason Cantarella's user avatar
1 vote
0 answers
110 views

Tail bound without independence

Suppose $X_i , X_j\in \mathbb{R}^d$ are gaussian vectors and $A$ is an $n\times n$ symmetric PSD matrix where $A_{ij} = f(\|X_i-X_j\|_2), \quad i,j\in 1,\ldots,n\;$ for some non-negative Lipschitz ...
ie86's user avatar
  • 195
1 vote
1 answer
122 views

Variance bound of a functional

$X_1,\ldots,X_n$ are i.i.d standard normal random variables. $a_1,\ldots, a_n$ are constants with $a_i \in [\kappa_1, \kappa_2]$ for all $i$ and $\kappa_1>0$. $\hat c_n$ is given as the solution ...
Gourab Mukherjee's user avatar
5 votes
1 answer
372 views

What are some of results in low dimensional statistics that do not hold in high dimensions?

This question is partially inspired by the following MO post: What are some of the surprising results of finite sample statistical estimation? and current heated research front of high dimensional ...
Henry.L's user avatar
  • 8,071
5 votes
1 answer
295 views

Constructive Central Limit Theorem

Background: Let $\{a_i\}_{i=1}^n$ be i.i.d. random variables with zero-mean and unit variance, on a probability space $\Omega$. Define $$s_n=\frac{1}{\sqrt{n}}\sum_{i\leq n} a_i$$ Central limit ...
ecstasyofgold's user avatar
3 votes
0 answers
186 views

Anti-concentration for sum of t-wise independent uniform variables

Let $X_{1},\ldots,X_{n}$ be i.i.d. random variables, each variable is uniform over the set of integers $\{ 0,\ldots,D-1 \}$. Let $S = \sum_{i=1}^{n}X_{i}$. By ``small ball probability'', we have that ...
Daniel86's user avatar
  • 225
3 votes
2 answers
319 views

Concentration inequality of joint event over time of a submartingale

Consider a discrete time submartingale $X_n$ with bounded difference $|X_n-X_{n-1}|\leq c$. With Azuma inequality we have the concentration of a single time event as $$ P(X_t-X_0 \leq -t) \leq exp\...
Sung-En Chiu's user avatar
4 votes
0 answers
141 views

Is there an example that both Berry-Essen bound and DKW bound are attained?

The Berry-Essen bound stated that $$\sup _{{x\in {\mathbb R}}}\left|\widehat{F_{n}(x)}-\Phi (x)\right|\leq C_{0}\cdot \psi _{0}$$ where $\psi _{0}(n)={\Big (}{\textstyle \sum \limits _{{i=1}}^{n}\...
Henry.L's user avatar
  • 8,071
2 votes
2 answers
1k views

Lower bound on number of samples for an epsilon delta approximation matching the Chernoff bound

So we have two biased coins, one comes out head w.p. $1/2+\epsilon$ and the other w.p. $1/2-\epsilon$. How many times should we flip these two coins to be able to tell them apart w.p. at least $\delta$...
shahrzad haddadan's user avatar
2 votes
1 answer
508 views

Extension of Gordon's comparison inequality to subgaussian processes?

"Theorem A" in this paper by Y. Gordon: http://www.math.uiuc.edu/~mjunge/Comps/Gordonm.pdf is a comparison inequality for Gaussian processes: Is there an analogue of this result for subgaussian ...
axk's user avatar
  • 517
3 votes
0 answers
126 views

Concentration of sums of random matrices around the mean, in the Loewner order

Recently, I have found myself interested in concentration properties of random matrices. Specifically I would like to answer questions of the following sort Let $\{X_i\}_{i=1}^n$ be i.i.d. copies ...
Cain's user avatar
  • 393
5 votes
2 answers
397 views

Why sum of samples without replacement is more concentrated than with replacement?

Set $n\le N$. Suppose $x_1,...,x_n$ are uniformly random variables taking value in $[N]$ In addition, let ${y_1,...,y_n}$ be an $n-$subset of $[N]$ that is chosen uniformly random among all $N \choose ...
MR_BD's user avatar
  • 550
4 votes
0 answers
162 views

Concentration Inequality for Score Functions of Exponential Familty

Let $p$ be the density of a continuous one-parameter exponential family distribution on $\mathbb{R}$. We assume that $$p(x) = c(x)\cdot \exp\bigl [ x \cdot \theta - b(\theta ) \bigr ], $$ where $\...
Steve's user avatar
  • 1,127
2 votes
0 answers
140 views

Matrices with i.i.d. Heavy tail Columns

I'm wondering if there are any known results about minimum eigenvalue of matrices with i.i.d. heavy tailed columns. In particular, Theorem 5.62 of Roman Vershynin's notes (http://www-personal.umich....
mohi's user avatar
  • 859
0 votes
0 answers
102 views

Probability of random variable being lesser than the other

Say there are two independent random variables, $X$ and $Y$, and we have samples $\{x_1,\dots x_n\},\{y_1,\dots y_n\}$. I am interested in bounding the probability of the event $C = \mathbb{1}_{X<Y}...
AvidLearner's user avatar
6 votes
0 answers
554 views

a variation on Hanson-Wright inequality

The classic Hanson-Wright inequality states that for a Gaussian random vector $\mathbf{x}\in\mathbb{R}^n$ distributed as $\mathcal{N}(\mathbf{0},\mathbf{I})$ and $\mathbf{A}\in\mathbb{R}^{n\times n}$ ...
mohi's user avatar
  • 859
1 vote
0 answers
146 views

minimum eigenvalue of Katri-Rao product of two Gaussian matrices

Let $\mathbf{A}\in\mathbb{R}^{k\times n}$ and $\mathbf{B}\in\mathbb{R}^{d\times n}$ be independent matrices with i.i.d. $\mathcal{N}(0,1)$ entries. I'm interested in lower bounding the minimum ...
Anahita's user avatar
  • 363
7 votes
2 answers
594 views

Large deviation/concentration inequality for submartingale

Let $S_t = M_t + D_t$ be the sum of a martingale $\left(M_t\right)_{t=1,2,\ldots}$ and a predictable process $(D_t)_{t=1,2,\ldots}$ such that the variance of the increments of $M$ is uniformly bounded ...
Peter's user avatar
  • 355
3 votes
0 answers
372 views

On the precise concentration of permanent of $\pm1$ matrices

Obtain $M\in\{-1,+1\}^{n\times n}$ by unbiased coin flipping. What is known about the distribution of permanent $\mathsf{Perm}(M)$? It seems to be bimodal. Given a function $g(n)$ what is the ...
user avatar
3 votes
0 answers
451 views

concentration bounds on weighted multinomial sum

Consider i.i.d random vectors $Y_{1},..,Y_{n}$ and they are chosen uniformly at random from $\{e_{1},..,e_{L}\}$ where $e_{i}$ is a $L\times 1$ vector with $i$th component be 1 and the others be 0. ...
Cuize Han's user avatar
7 votes
0 answers
759 views

Product of two random Gaussian matrices - orthant probability

Let $X \in \mathbb{R}^{m \times n}$ and $Y \in \mathbb{R}^{n \times k} $ be two independent Gaussian random matrices, i.e., with entries independently sampled from $\mathcal{N}(0,1)$ (a normal ...
Daniel Soudry's user avatar
8 votes
1 answer
618 views

Violating the Lebesgue density theorem

Can anyone exhibit a finite-dimensional metric space (preferably, $R^d$) equipped with a measure that does not satisfy the conclusions of the Lebesgue Density Theorem? Such examples exist in infinite-...
Aryeh Kontorovich's user avatar
3 votes
1 answer
282 views

Longest runs and concentration of measure

Consider the longest runs $\ell_\sigma(x)$ of the pattern $\sigma$ for $\sigma\in \{0, 1, 01, 10, 001,\dots\}$ etc. in a binary sequence $x=x_1\dots x_n$. For example, $\ell_{001}(0001110010011001)=2$...
Bjørn Kjos-Hanssen's user avatar

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