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Let $K$ be a smooth convex set with volume one in $\BBR^d$. Choose $n$ random points in $K$ independently according to the uniform distribution. The convex hull of these points, denoted by $K_n$, is called a {\it random polytope}. We prove…

Probability · Mathematics 2007-05-23 Van Vu

We study the circumradius of the intersection of an $m$-dimensional ellipsoid $\mathcal E$ with semi-axes $\sigma_1\geq\dots\geq \sigma_m$ with random subspaces of codimension $n$. We find that, under certain assumptions on $\sigma$, this…

Functional Analysis · Mathematics 2024-10-15 Aicke Hinrichs , David Krieg , Erich Novak , Joscha Prochno , Mario Ullrich

Approximate a smooth convex body $K$ with nonvanishing curvature by the convex hull of $n$ independent random points sampled from its boundary $\partial K$. In case the points are distributed according to the optimal density, we prove that…

Probability · Mathematics 2025-08-25 Mathias Sonnleitner

To provide a solid analytic foundation for the module approach to conditional risk measures, our purpose is to establish a complete random convex analysis over random locally convex modules by simultaneously considering the two kinds of…

Functional Analysis · Mathematics 2015-11-11 Tiexin Guo , Shien Zhao , Xiaolin Zeng

We study the problem of approximating the mixed volume $V(P_1^{(\alpha_1)}, \dots, P_k^{(\alpha_k)})$ of an $k$-tuple of convex polytopes $(P_1, \dots, P_k)$, each of which is defined as the convex hull of at most $m_0$ points in…

Computational Geometry · Computer Science 2025-12-30 Hariharan Narayanan , Sourav Roy

In this work we study a class of random convex sets that "interpolate" between polytopes and zonotopes. These sets arise from considering a $q^{th}$-moment ($q\geq 1$) of an average of order statistics of $1$-dimensional marginals of a…

Metric Geometry · Mathematics 2017-01-06 David Alonso-Gutiérrez , Joscha Prochno

Let $X_1,\dots,X_n$ be i.i.d. log-concave random vectors in $\mathbb R^d$ with mean 0 and covariance matrix $\Sigma$. We study the problem of quantifying the normal approximation error for $W=n^{-1/2}\sum_{i=1}^nX_i$ with explicit…

Probability · Mathematics 2023-05-30 Xiao Fang , Yuta Koike

Approximating convex bodies is a fundamental question in geometry, which has a wide variety of applications. Given a convex body $K$ in $\textbf{R}^d$ for fixed $d$, the objective is to minimize the number of facets of an approximating…

Computational Geometry · Computer Science 2026-01-26 Sunil Arya , David M. Mount

The following class of problems arose out of vain attempts to show that the Pascal's triangle adic transformation has trivial spectrum. Partition a set of size $N$ into sets of size $S \equiv S(N)$ (ignoring leftovers). What is the…

Probability · Mathematics 2016-08-30 David Handelman

In this work, we introduce and develop a theory of convex drawings of the complete graph $K_n$ in the sphere. A drawing $D$ of $K_n$ is convex if, for every 3-cycle $T$ of $K_n$, there is a closed disc $\Delta_T$ bounded by $D[T]$ such…

Combinatorics · Mathematics 2022-09-16 Alan Arroyo , Dan McQuillan , R. Bruce Richter , Gelasio Salazar

The cross covariogram g_{K,L} of two convex sets K and L in R^n is the function which associates to each x in R^n the volume of the intersection of K and L+x. Very recently Averkov and Bianchi [AB] have confirmed Matheron's conjecture on…

Metric Geometry · Mathematics 2010-03-10 Gabriele Bianchi

In this paper we partially resolve Hall's conjecture about the distribution of random triangles. We consider the probability that three points chosen uniformly at random, in a bounded convex region of the plane, form an acute triangle.…

Probability · Mathematics 2019-06-21 Gabriel Khan

Let $k \geq 2$ be a constant. Given any $k$ convex polygons in the plane with a total of $n$ vertices, we present an $O(n\log^{2k-3}n)$ time algorithm that finds a translation of each of the polygons such that the area of intersection of…

Computational Geometry · Computer Science 2023-07-04 Hyuk Jun Kweon , Honglin Zhu

For a fixed $k\in\{1,\dots,d\}$ consider random vectors $X_0,\dots, X_{k}\in\mathbb R^d$ with an arbitrary spherically symmetric joint density function. Let $A$ be any non-singular $d\times d$ matrix. We show that the $k$-dimensional volume…

Probability · Mathematics 2019-08-08 Friedrich Götze , Anna Gusakova , Dmitry Zaporozhets

We prove asymptotic lower bounds on the variance of the number of vertices and missed area of random disc-polygons in convex discs whose boundary is $C_+^2$ smooth. The established lower bounds are of the same order as the upper bounds…

Metric Geometry · Mathematics 2026-04-09 Ferenc Fodor , Balázs Grünfelder , Viktor Vígh

In this survey, we discuss volumetric and combinatorial results concerning (mostly finite) intersections or unions of balls (mostly of equal radii) in the $d$-dimensional real vector space, mostly equipped with the Euclidean norm. Our first…

Metric Geometry · Mathematics 2025-12-30 Károly Bezdek , Zsolt Lángi , Márton Naszódi

Let $n\geq 1$, $K>0$, and let $X=(X_1,X_2,\dots,X_n)$ be a random vector in $\mathbb{R}^n$ with independent $K$--subgaussian components. We show that for every $1$--Lipschitz convex function $f$ in $\mathbb{R}^n$ (the Lipschitzness with…

Probability · Mathematics 2023-05-02 Han Huang , Konstantin Tikhomirov

Let $K$ be a convex pentagon in the plane and let $K_1$ be the pentagon bounded by the diagonals of $K$. It has been conjectured that the maximum of the ratio between the areas of $K_1$ and $K$ is reached when $K$ is an affine regular…

History and Overview · Mathematics 2018-12-20 Jacqueline Cho , Dan Ismailescu , Yiwon Kim , Andrew Woojong Lee

Having its origin in theoretical computer science, the Kannan-Lov\'asz-Simonovits (KLS) conjecture is one of the major open problems in asymptotic convex geometry and high-dimensional probability theory today. In this work, we establish a…

Probability · Mathematics 2020-03-26 David Alonso-Gutiérrez , Joscha Prochno , Christoph Thaele

The likelihood function of a finite mixture model is a non-convex function with multiple local maxima and commonly used iterative algorithms such as EM will converge to different solutions depending on initial conditions. In this paper we…

Machine Learning · Computer Science 2016-08-19 Elad Mezuman , Yair Weiss