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We present several refinements on the fluctuations of sequences of random vectors (with values in the Euclidean space $\mathbb{R}^d$) which converge after normalization to a multidimensional Gaussian distribution. More precisely we refine…

Probability · Mathematics 2022-03-04 Pierre-Loïc Méliot , Ashkan Nikeghbali

We derive the exact generating function for planar maps (genus zero fatgraphs) with vertices of arbitrary even valence and with two marked points at a fixed geodesic distance. This is done in a purely combinatorial way based on a bijection…

Statistical Mechanics · Physics 2010-04-05 J. Bouttier , P. Di Francesco , E. Guitter

Real-world signals typically span across multiple dimensions, that is, they naturally reside on multi-way data structures referred to as tensors. In contrast to standard ``flat-view'' multivariate matrix models which are agnostic to data…

Signal Processing · Electrical Eng. & Systems 2019-12-04 Bruno Scalzo Dees , Anh-Huy Phan , Danilo P. Mandic

We show quantitative stability results for the geometric "cells" arising in semi-discrete optimal transport problems. Our results show two types of stability, the first is stability of the associated Laguerre cells in measure, without any…

Analysis of PDEs · Mathematics 2021-02-11 Mohit Bansil , Jun Kitagawa

The region of entropic vectors is a convex cone that has been shown to be at the core of many fundamental limits for problems in multiterminal data compression, network coding, and multimedia transmission. This cone has been shown to be…

Information Theory · Computer Science 2015-12-11 Yunshu Liu , John MacLaren Walsh

We bound the variance and other moments of a random vector based on the range of its realizations, thus generalizing inequalities of Popoviciu (1935) and Bhatia and Davis (2000) concerning measures on the line to several dimensions. This is…

Probability · Mathematics 2020-02-03 Tongseok Lim , Robert J. McCann

Given $n$ independent random marked $d$-vectors (points) $X_i$ distributed with a common density, define the measure $\nu_n=\sum_i\xi_i$, where $\xi_i$ is a measure (not necessarily a point measure) which stabilizes; this means that $\xi_i$…

Statistics Theory · Mathematics 2009-09-29 Mathew D. Penrose

Chance constraints describe a set of given random inequalities depending on the decision vector satisfied with a large enough probability. They are widely used in decision making under uncertain data in many engineering problems. This paper…

Optimization and Control · Mathematics 2025-04-01 Heng Zhang , Abdel Lisser

Max stable laws are limit laws of linearly normalized partial maxima of indepen- dent, identically distributed (iid) random variables (rvs). These are analogous to stable laws which are limit laws of normalized partial sums of iid rvs. In…

Statistics Theory · Mathematics 2016-11-25 Sreenivasan Ravi , Ali Saeb

A general theory is provided delivering convergence of maximal cyclically monotone mappings containing the supports of coupling measures of sequences of pairs of possibly random probability measures on Euclidean space. The theory is based…

Statistics Theory · Mathematics 2022-08-05 Johan Segers

Let $V$ be a finite nonempty set. A transit function is a map $R:V\times V\rightarrow 2^V$ such that $R(u,u)=\{u\}$, $R(u,v)=R(v,u)$ and $u\in R(u,v)$ hold for every $u,v\in V$. A set $K\subseteq V$ is $R$-convex if $R(u,v)\subset K$ for…

Combinatorics · Mathematics 2024-06-04 Manoj Changat , Lekshmi Kamal K. Sheela , Iztok Peterin , Ameera Vaheeda Shanavas

When modeling a vector of risk variables, extreme scenarios are often of special interest. The peaks-over-thresholds method hinges on the notion that, asymptotically, the excesses over a vector of high thresholds follow a multivariate…

Statistics Theory · Mathematics 2024-09-23 Anas Mourahib , Anna Kiriliouk , Johan Segers

Random geometric networks consist of 1) a set of nodes embedded randomly in a bounded domain $\mathcal{V} \subseteq \mathbb{R}^d$ and 2) links formed probabilistically according to a function of mutual Euclidean separation. We quantify how…

Social and Information Networks · Computer Science 2016-11-17 Alexander P. Kartun-Giles , Orestis Georgiou , Carl P. Dettmann

Many problems in dynamic data driven modeling deals with distributed rather than lumped observations. In this paper, we show that the Monge-Kantorovich optimal transport theory provides a unifying framework to tackle such problems in the…

Systems and Control · Computer Science 2014-02-10 Abhishek Halder , Raktim Bhattacharya

This paper investigates the robust optimal control of sampled-data stochastic systems with multiplicative noise and distributional ambiguity. We consider a class of discrete-time optimal control problems where the controller \emph{jointly}…

Optimization and Control · Mathematics 2026-02-05 Chung-Han Hsieh

We derive tight expressions for the maximum number of $k$-faces, $0\le{}k\le{}d-1$, of the Minkowski sum, $P_1\oplus{}P_2$, of two $d$-dimensional convex polytopes $P_1$ and $P_2$, as a function of the number of vertices of the polytopes.…

Computational Geometry · Computer Science 2011-10-04 Menelaos I. Karavelas , Eleni Tzanaki

Let $X$ be a $d$-dimensional random vector and $X_\theta$ its projection onto the span of a set of orthonormal vectors $\{\theta_1,...,\theta_k\}$. Conditions on the distribution of $X$ are given such that if $\theta$ is chosen according to…

Probability · Mathematics 2011-02-16 Elizabeth Meckes

In the maximum independent set of convex polygons problem, we are given a set of $n$ convex polygons in the plane with the objective of selecting a maximum cardinality subset of non-overlapping polygons. Here we study a special case of the…

Computational Geometry · Computer Science 2024-02-13 Fabrizio Grandoni , Edin Husić , Mathieu Mari , Antoine Tinguely

We investigate the asymptotic properties of random polytopes arising as convex hulls of $n$ independent random points sampled from a family of block-beta distributions. Notably, this family includes the uniform distribution on a product of…

Probability · Mathematics 2024-12-02 Florian Besau , Anna Gusakova , Christoph Thäle

This paper studies estimation of and inference on a distribution function $F$ that is concave on the nonnegative half line and admits a density function $f$ with potentially unbounded support. When $F$ is strictly concave, we show that the…

Statistics Theory · Mathematics 2019-11-12 Zheng Fang
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