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In many robotics applications, it is necessary to compute not only the distance between the robot and the environment, but also its derivative - for example, when using control barrier functions. However, since the traditional Euclidean…

The \emph{distance-number} of a graph $G$ is the minimum number of distinct edge-lengths over all straight-line drawings of $G$ in the plane. This definition generalises many well-known concepts in combinatorial geometry. We consider the…

Combinatorics · Mathematics 2008-09-09 Paz Carmi , Vida Dujmović , Pat Morin , David R. Wood

We generalize the asymptotic behavior of the graph distance between two uniformly chosen nodes in the configuration model to a wide class of random graphs. Among others, this class contains the Poissonian random graph, the expected degree…

Probability · Mathematics 2008-05-19 Henri van den Esker , Remco van der Hofstad , Gerard Hooghiemstra

New upper bounds on the relative entropy are derived as a function of the total variation distance. One bound refines an inequality by Verd\'{u} for general probability measures. A second bound improves the tightness of an inequality by…

Information Theory · Computer Science 2015-04-14 Igal Sason

This study investigates the extension of distance variance, a validated spread metric for continuous and binary variables [Edelmann et al., 2020, Ann. Stat., 48(6)], to quantify the spread of general categorical variables. We provide both…

Methodology · Statistics 2024-05-14 Qingyang Zhang

A bound for functional $\Delta(F)=\sup_{x\in\mathbb R}|F(x)-\Phi(x)|$ is obtained, which is uniform for all distribution functions $F$ of random variables with zero mean-value and unity variance. Moreover, a two-point distribution is found,…

Probability · Mathematics 2007-10-19 V. I. Chebotarev , A. S. Kondrik , K. V. Mikhaylov

We study a family of distance functions on rankings that allow for asymmetric treatments of alternatives and consider the distinct relevance of the top and bottom positions for ordered lists. We provide a full axiomatic characterization of…

Computer Science and Game Theory · Computer Science 2024-03-28 Andrea Aveni , Ludovico Crippa , Giulio Principi

The $f$-divergence is a fundamental notion that measures the difference between two distributions. In this paper, we study the problem of approximating the $f$-divergence between two Ising models, which is a generalization of recent work on…

Data Structures and Algorithms · Computer Science 2025-09-08 Weiming Feng , Yucheng Fu

We study the problem of generalized uniformity testing \cite{BC17} of a discrete probability distribution: Given samples from a probability distribution $p$ over an {\em unknown} discrete domain $\mathbf{\Omega}$, we want to distinguish,…

Data Structures and Algorithms · Computer Science 2017-09-08 Ilias Diakonikolas , Daniel M. Kane , Alistair Stewart

Labelled Markov chains (LMCs) are widely used in probabilistic verification, speech recognition, computational biology, and many other fields. Checking two LMCs for equivalence is a classical problem subject to extensive studies, while the…

Logic in Computer Science · Computer Science 2014-05-16 Taolue Chen , Stefan Kiefer

Consider a sequence of polynomials of bounded degree evaluated in independent Gaussian, Gamma or Beta random variables. We show that, if this sequence converges in law to a nonconstant distribution, then (i) the limit distribution is…

Probability · Mathematics 2013-05-14 Ivan Nourdin , Guillaume Poly

This paper proposes a geometric estimator of dependency between a pair of multivariate samples. The proposed estimator of dependency is based on a randomly permuted geometric graph (the minimal spanning tree) over the two multivariate…

Machine Learning · Computer Science 2019-10-02 Salimeh Yasaei Sekeh , Alfred O. Hero

Let $\{X, X_{n}; n \geq 1\}$ be a sequence of i.i.d. non-degenerate real-valued random variables with $\mathbb{E}X^{2} < \infty$. Let $S_{n} = \sum_{i=1}^{n} X_{i}$, $n \geq 1$. Let $g(\cdot): ~[0, \infty) \rightarrow [0, \infty)$ be a…

Probability · Mathematics 2025-05-02 Deli Li , Yu Miao , Yongcheng Qi

Distance distributions are a key building block in stochastic geometry modelling of wireless networks and in many other fields in mathematics and science. In this paper, we propose a novel framework for analytically computing the closed…

Information Theory · Computer Science 2019-03-20 Ross Pure , Salman Durrani , Fei Tong , Jianping Pan

We first introduce a class of divergence measures between power spectral density matrices. These are derived by comparing the suitability of different models in the context of optimal prediction. Distances between "infinitesimally close"…

Optimization and Control · Mathematics 2016-11-18 Xianhua Jiang , Lipeng Ning , Tryphon T. Georgiou

Given two sets $x_1^{(1)},\ldots,x_{n_1}^{(1)}$ and $x_1^{(2)},\ldots,x_{n_2}^{(2)}\in\mathbb{R}^p$ (or $\mathbb{C}^p$) of random vectors with zero mean and positive definite covariance matrices $C_1$ and $C_2\in\mathbb{R}^{p\times p}$ (or…

Probability · Mathematics 2018-10-11 Romain Couillet , Malik Tiomoko , Steeve Zozor , Eric Moisan

We explore the question asking for graphs $G$ for which the total distance decreases, possibly by a fixed constant $k$, upon the removal of any of its vertices. We obtain results leading to intuition and doubts for the \v{S}olt\'es' problem…

Combinatorics · Mathematics 2024-06-06 Stijn Cambie

Given two distributions $\mathcal{P}$ and $\mathcal{Q}$ over a high-dimensional domain $\{0,1\}^n$, and a parameter $\varepsilon$, the goal of distance estimation is to determine the statistical distance between $\mathcal{P}$ and…

Data Structures and Algorithms · Computer Science 2025-09-09 Gunjan Kumar , Kuldeep S. Meel , Yash Pote

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

Let $G$ be a connected graph of order $n$. The eccentricity $e(v)$ of a vertex $v$ is the distance from $v$ to a vertex farthest from $v$. The average eccentricity of $G$ is the mean of all eccentricities in $G$. We give upper bounds on the…

Combinatorics · Mathematics 2020-08-06 Fadekemi Janet Osaye