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Consider $d+2$ i.i.d. random points $X_1,\ldots, X_{d+2}$ in $\mathbb R^d$. In this note, we compute the probability that their convex hull is a simplex focusing on three specific distributional settings: (i) the distribution of $X_1$ is…

Probability · Mathematics 2025-06-03 Anna Gusakova , Zakhar Kabluchko

Let $\mu$ be a probability distribution on $\mathbb{R}^d$ which assigns measure zero to every hyperplane and $S$ a set of points sampled independently from $\mu$. What can be said about the expected combinatorial structure of the convex…

Probability · Mathematics 2023-07-13 Brett Leroux

Let n points be chosen randomly and independently in the unit disk. "Sylvester's question" concerns the probability p_n that they are the vertices of a convex n-sided polygon. Here we establish the link with another problem. We show that…

Statistical Mechanics · Physics 2010-08-26 H. J. Hilhorst , P. Calka , G. Schehr

We consider the convex optimization problem $\min \{f(x) : g_j(x)\leq 0, j=1,...,m\}$ where $f$ is convex, the feasible set K is convex and Slater's condition holds, but the functions $g_j$ are not necessarily convex. We show that for any…

Optimization and Control · Mathematics 2009-11-09 Jean B. Lasserre

Denote by ${\mathcal K}^d$ the family of convex bodies in $E^d$ and by $w(C)$ the minimal width of $C \in {\mathcal K}^d$. We ask for the greatest number $\Lambda_n ({\mathcal K}^d)$ such that every $C \in {\mathcal K}^d$ contains a…

Metric Geometry · Mathematics 2017-03-30 Marek Lassak

The $K$-hull of a compact set $A\subset\mathbb{R}^d$, where $K\subset \mathbb{R}^d$ is a fixed compact convex body, is the intersection of all translates of $K$ that contain $A$. A set is called $K$-strongly convex if it coincides with its…

Metric Geometry · Mathematics 2021-10-06 Alexander Marynych , Ilya Molchanov

We review several (and provide new) results on the theory of moments, sums of squares and basic semi-algebraic sets when convexity is present. In particular, we show that under convexity, the hierarchy of semidefinite relaxations for…

Optimization and Control · Mathematics 2008-12-04 Jean B. Lasserre

Approximating convex bodies succinctly by convex polytopes is a fundamental problem in discrete geometry. A convex body $K$ of diameter $\mathrm{diam}(K)$ is given in Euclidean $d$-dimensional space, where $d$ is a constant. Given an error…

Computational Geometry · Computer Science 2018-01-11 Sunil Arya , Guilherme D. da Fonseca , David M. Mount

A natural model for the approximation of a convex body $K$ in $\mathbb{R}^d$ by random polytopes is obtained as follows. Take a stationary Poisson hyperplane process in the space, and consider the random polytope $Z_K$ defined as the…

Probability · Mathematics 2019-08-27 Daniel Hug , Rolf Schneider

The Weber problem consists of finding a point in $\mathbbm{R}^n$ that minimizes the weighted sum of distances from $m$ points in $\mathbbm{R}^n$ that are not collinear. An application that motivated this problem is the optimal location of…

Optimization and Control · Mathematics 2015-03-20 Germán A. Torres

Let $\mathbb{P}_K(n)$ be the probability that $n$ points $z_1,\ldots,z_n$ picked uniformly and independently in $K$, a non-flat compact convex polygon in $\mathbb{R}^2$, are in convex position, that is, form the vertex set of a convex…

Probability · Mathematics 2026-05-19 Ludovic Morin

Motivated by work of Zhang from the early `90s, Medvedev and Scanlon formulated the following conjecture. Let $K$ be an algebraically closed field of characteristic $0$ and let $X$ be a quasiprojective variety defined over $K$ endowed with…

Algebraic Geometry · Mathematics 2016-10-24 Jason P. Bell , Dragos Ghioca , Zinovy Reichstein , Matthew Satriano

Let ${\bf K} = (K_1, ..., K_n)$ be an $n$-tuple of convex compact subsets in the Euclidean space $\R^n$, and let $V(\cdot)$ be the Euclidean volume in $\R^n$. The Minkowski polynomial $V_{{\bf K}}$ is defined as $V_{{\bf K}}(\lambda_1, ...…

Computational Geometry · Computer Science 2009-01-19 Leonid Gurvits

We investigate the problem of the number of flats simultaneously tangent to several convex hypersurfaces in real projective space from a random point of view. More precisely, we say that smooth convex hypersurfaces $X_1, \ldots,…

Algebraic Geometry · Mathematics 2018-01-22 Khazhgali Kozhasov , Antonio Lerario

We show that the problem of finding the simplex of largest volume in the convex hull of $n$ points in $\mathbb{Q}^d$ can be approximated with a factor of $O(\log d)^{d/2}$ in polynomial time. This improves upon the previously best known…

Computational Geometry · Computer Science 2014-06-16 Marco Di Summa , Friedrich Eisenbrand , Yuri Faenza , Carsten Moldenhauer

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 show that for any compact convex set $K$ in $\mathbb{R}^d$ and any finite family $\mathcal{F}$ of convex sets in $\mathbb{R}^d$, if the intersection of every sufficiently small subfamily of $\mathcal{F}$ contains an isometric copy of $K$…

Metric Geometry · Mathematics 2020-10-09 John A. Messina , Pablo Soberón

Recall that a convex body $K$ is in John's position if the unit Euclidean ball is the maximal volume ellipsoid contained in $K$. Approximating convex body in John's position by polytopes we obtain the following results. 1. Let $n>R_n\ge 1$…

Metric Geometry · Mathematics 2019-08-19 Han Huang

In this paper, we consider the maximization of a probability $\mathbb{P}\{ \zeta \mid \zeta \in \mathbf{K}(\mathbf x)\}$ over a closed and convex set $\mathcal X$, a special case of the chance-constrained optimization problem. We define…

Optimization and Control · Mathematics 2022-03-11 Ibrahim E. Bardakci , Afrooz Jalilzadeh , Constantino Lagoa , Uday V. Shanbhag

We study the problem of approximating the cone of positive semidefinite (PSD) matrices with a cone that can be described by smaller-sized PSD constraints. Specifically, we ask the question: "how closely can we approximate the set of…

Optimization and Control · Mathematics 2022-09-08 Dogyoon Song , Pablo A. Parrilo