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Intrinsic volumes are fundamental geometric invariants generalizing volume, surface area, and mean width for convex bodies. We establish a unified Laplace-Grassmannian representation for intrinsic and dual volumes of convex polynomial…

Metric Geometry · Mathematics 2025-11-04 Trí Minh Lê , Khai-Hoan Nguyen-Dang

We introduce and explore a new concept of evasive subspace with respect to a collection of subspaces sharing a common dimension, most notably partial spreads. We show that this concept generalises known notions of subspace scatteredness and…

Combinatorics · Mathematics 2023-10-17 Anina Gruica , Alberto Ravagnani , John Sheekey , Ferdinando Zullo

We propose a framework for descriptively analyzing sets of partial orders based on the concept of depth functions. Despite intensive studies of depth functions in linear and metric spaces, there is very little discussion on depth functions…

Machine Learning · Computer Science 2024-02-12 Hannah Blocher , Georg Schollmeyer , Christoph Jansen , Malte Nalenz

Motivated by the geometric reduction of Cauchy--Szeg\H{o} projections on quadratic surfaces of higher codimension (Nagel--Ricci--Stein, 2001) and recent developments on the real-variable theory adapted to twisted multiparameter structures…

Classical Analysis and ODEs · Mathematics 2026-04-03 Ji Li , Chong-Wei Liang , Chaojie Wen , Qingyan Wu

We prove that for a continuum $K\subset \mathbb R^n$ the sum $K^{+n}$ of $n$ copies of $K$ has non-empty interior in $\mathbb R^n$ if and only if $K$ is not flat in the sense that the affine hull of $K$ coincides with $\mathbb R^n$.…

General Topology · Mathematics 2020-04-09 Taras Banakh , Eliza Jabłońska , Wojciech Jabłoński

We establish the first partial regularity results for (strongly) symmetric quasiconvex functionals of linear growth on BD, the space of functions of bounded deformation. By Rindler's foundational work (Lower semicontinuity for integral…

Analysis of PDEs · Mathematics 2020-10-07 Franz Gmeineder

The geometric median, a notion of center for multivariate distributions, has gained recent attention in robust statistics and machine learning. Although conceptually distinct from the mean (i.e., expectation), we demonstrate that both are…

Statistics Theory · Mathematics 2026-02-19 Richard Schwank , Mathias Drton

In this paper, a new two-dimensional Hardy type inequality is given in terms of pseudo-analysis dealing with set-valued functions. The first one is given for a pseudo-integral of set-valued function where pseudo-addition and…

Functional Analysis · Mathematics 2022-06-29 Bayaz Daraby , Mortaza Tahmourasi , Asghar Rahimi

Under special conditions on data set and underlying distribution, the limit of finite sample breakdown point of Tukey's halfspace median ($\frac{1} {3}$) has been obtained in literature. In this paper, we establish the result under…

Statistics Theory · Mathematics 2016-04-26 Xiaohui Liu , Shihua Luo , Yijun Zuo

The coordinate-wise median is a classic and most well-studied strategy-proof mechanism in social choice and facility location scenarios. Surprisingly, there is no systematic study of its approximation ratio in $d$-dimensional spaces. The…

Computer Science and Game Theory · Computer Science 2025-02-14 Nick Gravin , Jianhao Jia

We study the action of translation on the spaces of uniformly bounded continuous functions on the real line which are uniformly band-limited in a compact interval. We prove that two intervals themselves will decide if two spaces are…

Dynamical Systems · Mathematics 2022-10-05 Lei Jin , Yixiao Qiao , Siming Tu

In this paper we define an addition operation on the class of quasi-concave functions. While the new operation is similar to the well-known sup-convolution, it has the property that it polarizes the Lebesgue integral. This allows us to…

Functional Analysis · Mathematics 2012-10-17 Vitali Milman , Liran Rotem

Distribution function is essential in statistical inference, and connected with samples to form a directed closed loop by the correspondence theorem in measure theory and the Glivenko-Cantelli and Donsker properties. This connection creates…

Methodology · Statistics 2024-04-02 Xueqin Wang , Jin Zhu , Wenliang Pan , Junhao Zhu , Heping Zhang

We show that a random concave function having a periodic hessian on an equilateral lattice has a quadratic scaling limit, if the average hessian of the function satisfies certain conditions. We consider the set of all concave functions $g$…

Probability · Mathematics 2020-04-24 Hariharan Narayanan

We present a new algorithm for Tukey (halfspace) depth level sets and its implementation. Given $d$-dimensional data set for any $d\geq 2$, the algorithm is based on representation of level sets as intersections of balls in $R^d$, and can…

Computational Geometry · Computer Science 2016-11-16 Milica Bogicevic , Milan Merkle

We propose a novel measure of statistical depth, the metric spatial depth, for data residing in an arbitrary metric space. The measure assigns high (low) values for points located near (far away from) the bulk of the data distribution,…

Statistics Theory · Mathematics 2023-06-19 Joni Virta

The variance conjecture in Asymptotic Convex Geometry stipulates that the Euclidean norm of a random vector uniformly distributed in a (properly normalised) high-dimensional convex body $K\subset {\mathbb R}^n$ satisfies a Poincar\'e-type…

Functional Analysis · Mathematics 2018-05-09 Beatrice-Helen Vritsiou

Robertson (1988) suggested a model for the realization space of a convex d-dimensional polytope and an approach via the implicit function theorem, which -- in the case of a full rank Jacobian -- proves that the realization space is a…

Metric Geometry · Mathematics 2020-07-02 Laith Rastanawi , Rainer Sinn , Günter M. Ziegler

It is proved that, if $(P_n)$ is a sequence of polynomials with complex coefficients having unbounded valences and tending to infinity at sufficiently many points, then there is an infinite dimensional closed subspace of entire functions,…

Complex Variables · Mathematics 2025-01-17 L. Bernal-González , M. C. Calderón-Moreno , J. López-Salazar , J. A. Prado-Bassas

In this paper we develop a very general class of bivariate discrete distributions. The basic idea is very simple. The marginals are obtained by taking the random geometric sum of a baseline distribution function. The proposed class of…

Methodology · Statistics 2018-05-22 Debasis Kundu
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