English
Related papers

Related papers: Diversities and the Generalized Circumradius

200 papers

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

Algebras of generalized functions offer possibilities beyond the purely distributional approach in modelling singular quantities in non-smooth differential geometry. This article presents an introductory survey of recent developments in…

Functional Analysis · Mathematics 2007-05-23 Michael Kunzinger

Fix a space dimension $d\ge 2$, parameters $\alpha > -1$ and $\beta \ge 1$, and let $\gamma_{d,\alpha, \beta}$ be the probability measure of an isotropic random vector in $\mathbb{R}^d$ with density proportional to \begin{align*}…

Probability · Mathematics 2018-08-30 Julian Grote

The longstanding Godbersen's conjecture states that for any convex body $K \subset \mathbb R^n$ of volume $1$ and any $j \in \{0, \ldots, n\}$, the mixed volume $V_j = V(K[j], -K[n - j])$ is bounded by $\binom{n}{j}$, with equality if and…

Metric Geometry · Mathematics 2024-12-10 Shiri Artstein-Avidan , Eli Putterman

Using commutative algebra methods we study the generalized minimum distance function (gmd function) and the corresponding generalized footprint function of a graded ideal in a polynomial ring over a field. The number of solutions that a…

Commutative Algebra · Mathematics 2019-10-23 Manuel Gonzalez-Sarabia , Jose Martínez-Bernal , Rafael H. Villarreal , Carlos E. Vivares

We study two notions. One is that of spindle convexity. A set of circumradius not greater than one is spindle convex if, for any pair of its points, it contains every short circular arc of radius at least one, connecting them. The other…

Metric Geometry · Mathematics 2011-10-20 Karoly Bezdek , Zsolt Langi , Marton Naszodi , Peter Papez

We consider the problem of minimizing the relative perimeter under a volume constraint in an unbounded convex body $C\subset \mathbb{R}^{n+1}$, without assuming any further regularity on the boundary of $C$. Motivated by an example of an…

Metric Geometry · Mathematics 2016-06-27 Gian Paolo Leonardi , Manuel Ritoré , Efstratios Vernadakis

In 2000, A. Koldobsky asked whether two types of generalizations of the notion of an intersection-body, are in fact equivalent. The structures of these two types of generalized intersection-bodies have been studied by the author in…

Functional Analysis · Mathematics 2007-05-23 Emanuel Milman

Let $K$ be a centrally-symmetric convex body in $\mathbb{R}^n$ and let $\|\cdot\|$ be its induced norm on ${\mathbb R}^n$. We show that if $K \supseteq r B_2^n$ then: \[ \sqrt{n} M(K) \leqslant C \sum_{k=1}^{n} \frac{1}{\sqrt{k}}…

Functional Analysis · Mathematics 2016-02-02 Apostolos Giannopoulos , Emanuel Milman

G\"ahler ([3],[4]) introduced the concept of 2-metric as a possible generalization of usual notion of a metric space. In many cases the results obtained in the usual metric spaces and 2-metric spaces are found to be unrelated (see [5]).…

Classical Analysis and ODEs · Mathematics 2018-09-25 Kamran Alam Khan

A key idea in convex optimization theory is to use well-structured affine functions to approximate general functions, leading to impactful developments in conjugate functions and convex duality theory. This raises the question: what are the…

Optimization and Control · Mathematics 2025-04-22 Ningji Wei

Suppose that $K \subseteq \RR^d$ is a 0-symmetric convex body which defines the usual norm $$ \Norm{x}_K = \sup\Set{t\ge 0: x \notin tK} $$ on $\RR^d$. Let also $A\subseteq\RR^d$ be a measurable set of positive upper density $\rho$. We show…

Classical Analysis and ODEs · Mathematics 2007-05-23 Mihail N. Kolountzakis

Similarity learning has received a large amount of interest and is an important tool for many scientific and industrial applications. In this framework, we wish to infer the distance (similarity) between points with respect to an arbitrary…

Machine Learning · Statistics 2016-11-30 Michael Rabadi

We consider distributions on a closed compact manifold $M$ as maps on smoothing operators. Thus spaces of certain maps between $\Psi^{-\infty}(M)\to \mathcal{C}^{\infty}(M)$ are considered as generalized functions. For any collection of…

Analysis of PDEs · Mathematics 2009-06-09 Shantanu Dave

In the present paper, we give a q-analogue of the Grothendieck conjecture on p-curvatures for q-difference equations defined over the field of rational function K(x), where K is a finite extension of a field of rational functions k(q), with…

Quantum Algebra · Mathematics 2012-05-09 Lucia Di Vizio , Charlotte Hardouin

We introduce a family of symmetric convex bodies called generalized ellipsoids of degree $d$ (GE-$d$s), with ellipsoids corresponding to the case of $d=0$. Generalized ellipsoids (GEs) retain many geometric, algebraic, and algorithmic…

Optimization and Control · Mathematics 2025-07-01 Amir Ali Ahmadi , Abraar Chaudhry , Cemil Dibek

We establish a result which states that regularizing an inverse problem with the gauge of a convex set $C$ yields solutions which are linear combinations of a few extreme points or elements of the extreme rays of $C$. These can be…

Optimization and Control · Mathematics 2018-12-12 Claire Boyer , Antonin Chambolle , Yohann de Castro , Vincent Duval , Frédéric de Gournay , Pierre Weiss

We define the algebra of Colombeau generalized functions on the space of generalized points of {\mathbb R}^d which naturally contains the tempered generalized functions. The subalgebra of \mathscr{S}-regular generalized functions of this…

Functional Analysis · Mathematics 2017-05-24 Hans Vernaeve

Geometric quantiles are popular location functionals to build rank-based statistical procedures in multivariate settings. They are obtained through the minimization of a non-smooth convex objective function. As a result, the singularity of…

Statistics Theory · Mathematics 2026-02-11 Dimitri Konen , Gilles Stupfler

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
‹ Prev 1 3 4 5 6 7 10 Next ›