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A strong law of large numbers for $d$-dimensional random projections of the $n$-dimensional cube is derived. It shows that with respect to the Hausdorff distance a properly normalized random projection of $[-1,1]^n$ onto $\mathbb{R}^d$…

Probability · Mathematics 2019-10-08 Zakhar Kabluchko , Joscha Prochno , Christoph Thaele

We prove that the uniform probability measure $\mu$ on every $(n-k)$-dimensional projection of the $n$-dimensional unit cube verifies the variance conjecture with an absolute constant $C$ $$\textrm{Var}_\mu|x|^2\leq C \sup_{\theta\in…

Functional Analysis · Mathematics 2017-03-30 David Alonso-Gutiérrez , Julio Bernués

Accurate estimation of tail probabilities of projections of high-dimensional probability measures is of relevance in high-dimensional statistics and asymptotic geometric analysis. Whereas large deviation principles identify the asymptotic…

Probability · Mathematics 2023-04-25 Yin-Ting Liao , Kavita Ramanan

Suppose X is a random vector, that is distributed uniformly in some n-dimensional convex set. It was conjectured that when the dimension n is very large, there exists a non-zero vector u, such that the distribution of the real random…

Metric Geometry · Mathematics 2009-11-11 B. Klartag

Let $X$ be a $d$-dimensional random vector and $X_\theta$ its projection onto the span of a set of orthonormal vectors $\{\theta_1,...,\theta_k\}$. Conditions on the distribution of $X$ are given such that if $\theta$ is chosen according to…

Probability · Mathematics 2011-02-16 Elizabeth Meckes

Given an $n$-dimensional random vector $X^{(n)}$ , for $k < n$, consider its $k$-dimensional projection $\mathbf{a}_{n,k}X^{(n)}$, where $\mathbf{a}_{n,k}$ is an $n \times k$-dimensional matrix belonging to the Stiefel manifold…

Probability · Mathematics 2021-05-12 Steven Soojin Kim , Kavita Ramanan

This paper investigates the rate-distortion function, under a squared error distortion $D$, for an $n$-dimensional random vector uniformly distributed on an $(n-1)$-sphere of radius $R$. First, an expression for the rate-distortion function…

Information Theory · Computer Science 2024-01-10 Alex Dytso , Martina Cardone

We consider products of uniform random variables from the Stiefel manifold of orthonormal $k$-frames in $\mathbb{R}^n$, $k \le n$, and random vectors from the $n$-dimensional $\ell_p^n$-ball $\mathbb{B}_p^n$ with certain $p$-radial…

Probability · Mathematics 2022-03-02 Tom Kaufmann , Holger Sambale , Christoph Thäle

We consider the problem of estimating the mean of a random vector based on $N$ independent, identically distributed observations. We prove the existence of an estimator that has a near-optimal error in all directions in which the variance…

Statistics Theory · Mathematics 2020-10-23 Gabor Lugosi , Shahar Mendelson

The projected normal distribution, also known as the angular Gaussian distribution, is obtained by dividing a multivariate normal random variable $\mathbf{x}$ by its norm $\sqrt{\mathbf{x}^T \mathbf{x}}$. The resulting random variable…

Methodology · Statistics 2025-06-24 Daniel Herrera-Esposito , Johannes Burge

We give a nearly-optimal algorithm for testing uniformity of distributions supported on $\{-1,1\}^n$, which makes $\tilde O (\sqrt{n}/\varepsilon^2)$ queries to a subcube conditional sampling oracle (Bhattacharyya and Chakraborty (2018)).…

Data Structures and Algorithms · Computer Science 2021-02-08 Clément L. Canonne , Xi Chen , Gautam Kamath , Amit Levi , Erik Waingarten

The paper provides a description of the large deviation behavior for the Euclidean norm of projections of $\ell_p^n$-balls to high-dimensional random subspaces. More precisely, for each integer $n\geq 1$, let $k_n\in\{1,\ldots,n-1\}$,…

Probability · Mathematics 2017-06-20 David Alonso-Gutiérrez , Joscha Prochno , Christoph Thaele

The empirical mean of $n$ independent and identically distributed (i.i.d.) random variables $(X_1,\dots,X_n)$ can be viewed as a suitably normalized scalar projection of the $n$-dimensional random vector $X^{(n)}\doteq(X_1,\dots,X_n)$ in…

Probability · Mathematics 2015-10-07 Nina Gantert , Steven Soojin Kim , Kavita Ramanan

Let $p\in[1,\infty]$. Consider the projection of a uniform random vector from a suitably normalized $\ell^p$ ball in $\mathbb{R}^n$ onto an independent random vector from the unit sphere. We show that sequences of such random projections,…

Probability · Mathematics 2015-12-17 Nina Gantert , Steven Soojin Kim , Kavita Ramanan

Let X be a real or complex Hilbert space of finite but large dimension d, let S(X) denote the unit sphere of X, and let u denote the normalized uniform measure on S(X). For a finite subset B of S(X), we may test whether it is approximately…

Probability · Mathematics 2019-08-01 Sheldon Goldstein , Joel L. Lebowitz , Roderich Tumulka , Nino Zanghi

In this paper, we consider a strongly-repelling model of $n$ ordered particles $\{e^{i \theta_j}\}_{j=0}^{n-1}$ with the density $p({\theta_0},\cdots, \theta_{n-1})=\frac{1}{Z_n} \exp \left\{-\frac{\beta}{2}\sum_{j \neq k} \sin^{-2} \left(…

Probability · Mathematics 2018-05-30 Alexander Soshnikov , Yuanyuan Xu

One of the fundamental theorems of uniform distribution theory states that the fractional parts of the sequence $(n \alpha)_{n \geq 1}$ are uniformly distributed modulo one (u.d. mod 1) for every irrational number $\alpha$. Another…

Number Theory · Mathematics 2015-02-26 Christoph Aistleitner , Roswitha Hofer , Gerhard Larcher

Random integers, sampled uniformly from $[1,x]$, share similarities with random permutations, sampled uniformly from $S_n$. These similarities include the Erd\H{o}s--Kac theorem on the distribution of the number of prime factors of a random…

Number Theory · Mathematics 2024-10-04 Dor Elboim , Ofir Gorodetsky

Every element $\theta=(\theta_1,\ldots,\theta_n)$ of the probability $n$-simplex induces a probability distribution $P_\theta$ of a random variable $X$ that can assume only a finite number of real values $x_1 < \cdots < x_n$ by defining…

Probability · Mathematics 2020-09-08 S. Fried

We study the problem of generalized uniformity testing \cite{BC17} of a discrete probability distribution: Given samples from a probability distribution $p$ over an {\em unknown} discrete domain $\mathbf{\Omega}$, we want to distinguish,…

Data Structures and Algorithms · Computer Science 2017-09-08 Ilias Diakonikolas , Daniel M. Kane , Alistair Stewart
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