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Let $\Omega$ be a bounded closed convex set in ${\mathbb R}^d$ with non-empty interior, and let ${\cal C}_r(\Omega)$ be the class of convex functions on $\Omega$ with $L^r$-norm bounded by $1$. We obtain sharp estimates of the…

Statistics Theory · Mathematics 2017-02-28 Fuchang Gao , Jon A. Wellner

Given a Borel measure $\mu$ on ${\mathbb R}^{n}$, we define a convex set by \[ M({\mu})=\bigcup_{\substack{0\le f\le1,\\ \int_{{\mathbb R}^{n}}f\,{\rm d}{\mu}=1 } }\left\{ \int_{{\mathbb R}^{n}}yf\left(y\right)\,{\rm…

Metric Geometry · Mathematics 2017-06-23 Han Huang , Boaz A. Slomka

We prove that any extended formulation that approximates the matching polytope on $n$-vertex graphs up to a factor of $(1+\varepsilon)$ for any $\frac2n \le \varepsilon \le 1$ must have at least $\binom{n}{{\alpha}/{\varepsilon}}$ defining…

Computational Complexity · Computer Science 2017-11-29 Makrand Sinha

We introduce a new generalization of relative entropy to non-negative vectors with sums $\gt 1$. We show in a purely combinatorial setting, with no probabilistic considerations, that in the presence of linear constraints defining a convex…

Information Theory · Computer Science 2024-05-08 Kostas N. Oikonomou

The approximate Carath\'eodory problem in general form is as follows: Given two symmetric convex bodies $P,Q \subseteq \mathbb{R}^m$, a parameter $k \in \mathbb{N}$ and $\mathbf{z} \in \textrm{conv}(X)$ with $X \subseteq P$, find…

Metric Geometry · Mathematics 2022-10-31 Victor Reis , Thomas Rothvoss

We provide a streamlined proof and improved estimates for the weak multivariate Gnedenko law of large numbers on concentration of random polytopes within the space of convex bodies (in a fixed or a high dimensional setting), as well as a…

Probability · Mathematics 2014-03-11 Daniel J. Fresen , Richard A. Vitale

We prove a version of the Bernstein-Walsh theorem on uniform polynomial approximation of holomorphic functions on compact sets in several complex variables. Here we consider subclasses of the full polynomial space associated to a convex…

Complex Variables · Mathematics 2017-01-23 Len Bos , Norm Levenberg

We introduce a new variant of quantitative Helly-type theorems: the minimal \emph{"homothetic distance"} of the intersection of a family of convex sets to the intersection of a subfamily of a fixed size. As an application, we establish the…

Metric Geometry · Mathematics 2021-11-03 Grigory Ivanov , Márton Naszódi

In the spirit of the Genetics of the Regular Figures, by L. Fejes T\'oth, we prove the following theorem: If $2n$ points are selected in the $n$-dimensional Euclidean ball $B^n$ so that the smallest distance between any two of them is as…

Metric Geometry · Mathematics 2007-05-23 Wlodzimierz Kuperberg

While there is extensive literature on approximation, deterministic as well as random, of general convex bodies $K$ in the symmetric difference metric, or other metrics arising from intrinsic volumes, very little is known for corresponding…

Metric Geometry · Mathematics 2025-08-25 Joscha Prochno , Carsten Schütt , Mathias Sonnleitner , Elisabeth M. Werner

We study the probability distribution of the area and the number of vertices of random polygons in a convex set $K\subset\mathbb{R}^2$. The novel aspect of our approach is that it yields uniform estimates for all convex sets…

Probability · Mathematics 2015-03-13 John Pardon

Let $K$ be a symmetric convex body in ${\mathbf R}^n$. It is well-known that for every $\theta\in (0,1)$ there exists a subspace $F$ of ${\mathbf R}^n$ with ${\rm dim}F= [(1-\theta )n]$ such that $${\mathcal P}_F(K)\supseteq…

Metric Geometry · Mathematics 2016-09-06 Apostolos A. Giannopoulos , Vitali D. Milman

We study density thresholds that force a measurable set $E\subseteq\mathbb{R}^d$ to contain all sufficiently large similar copies of every $n$-point configuration. We prove a lower bound of the form $1-O((\log n)/n)$, which matches the…

Classical Analysis and ODEs · Mathematics 2026-04-21 Vjekoslav Kovač , Adian Anibal Santos Sepčić

The symmetric convex hull of random points that are independent and distributed according to the cone probability measure on the $\ell_p$-unit sphere of $\mathbb R^n$ for some $1\leq p < \infty$ is considered. We prove that these random…

Functional Analysis · Mathematics 2017-03-14 Julia Hörrmann , Joscha Prochno , Christoph Thaele

In this short note, we prove a version of the Johnson-Lindenstrauss flattening Lemma for point sets taking values in discrete subgroups. More precisely, given $d,\lambda_0,N_0\in\mathbb{N}$ and $\epsilon\in \left(0,\frac{1}{2}\right)$…

Metric Geometry · Mathematics 2025-01-22 Rodolfo Viera

We consider the problem of sampling from a $d$-dimensional log-concave distribution $\pi(\theta) \propto \exp(-f(\theta))$ for $L$-Lipschitz $f$, constrained to a convex body with an efficiently computable self-concordant barrier function,…

Data Structures and Algorithms · Computer Science 2024-11-14 Yuzhou Gu , Nikki Lijing Kuang , Yi-An Ma , Zhao Song , Lichen Zhang

Given an irreducible variety $X$ over a finite field, the density of hypersurfaces of varying degree $d$ intersecting $X$ in an irreducible subvariety is $1$, by a result of Charles and Poonen. In this note, we analyse the situation fixing…

Algebraic Geometry · Mathematics 2020-02-11 Mehdi Makhul , Josef Schicho

Let $d$ be a nonnegative integer, and let $P \subset \mathbb R^d$ be a $d$-dimensional convex lattice polytope. In this article, we prove that the ratio of the volume of a normal-sized miniature of $P$ to that of $P$ is $1:\binom{2d+1}{d},$…

Combinatorics · Mathematics 2026-05-21 Takashi Hirotsu

We derive a central limit theorem for the number of vertices of convex polytopes induced by stationary Poisson hyperplane processes in $\mathbb{R}^d$. This result generalizes an earlier one proved by Paroux [Adv. in Appl. Probab. 30 (1998)…

Probability · Mathematics 2007-05-23 Lothar Heinrich , Hendrik Schmidt , Volker Schmidt

Let $p$ be an unknown and arbitrary probability distribution over $[0,1)$. We consider the problem of {\em density estimation}, in which a learning algorithm is given i.i.d. draws from $p$ and must (with high probability) output a…

Machine Learning · Computer Science 2014-11-04 Siu-On Chan , Ilias Diakonikolas , Rocco A. Servedio , Xiaorui Sun