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The Hausdorff distance is a measure of (dis-)similarity between two sets which is widely used in various applications. Most of the applied literature is devoted to the computation for sets consisting of a finite number of points. This has…

Metric Geometry · Mathematics 2020-09-22 Daniel Kraft

A new similarity measure for two sets of S-parameters is proposed. It is constructed with the modified Hausdorff distance applied to S-parameter points in 3D space with real, imaginary and normalized frequency axes. New S-parameters…

Mathematical Physics · Physics 2021-08-24 Yuriy Shlepnev

Motivated by Leinster-Cobbold measures of biodiversity, the notion of the spread of a finite metric space is introduced. This is related to Leinster's magnitude of a metric space. Spread is generalized to infinite metric spaces equipped…

Metric Geometry · Mathematics 2015-01-07 Simon Willerton

Most metrics between finite point measures currently used in the literature have the flaw that they do not treat differing total masses in an adequate manner for applications. This paper introduces a new metric $\bar{d}_1$ that combines…

Probability · Mathematics 2007-08-22 Dominic Schuhmacher , Aihua Xia

We study the problem of mean estimation for high-dimensional distributions, assuming access to a statistical query oracle for the distribution. For a normed space $X = (\mathbb{R}^d, \|\cdot\|_X)$ and a distribution supported on vectors $x…

Data Structures and Algorithms · Computer Science 2019-02-08 Jerry Li , Aleksandar Nikolov , Ilya Razenshteyn , Erik Waingarten

In these notes we generalize the notion of a (pseudo) metric measuring the distance of two points, to a (pseudo) n-metric which assigns a value to a tuple of n points. We present two principles of constructing pseudo n-metrics. The first…

Metric Geometry · Mathematics 2023-10-19 Wolf-Jürgen Beyn

We consider a high-dimensional mean estimation problem over a binary hidden Markov model, which illuminates the interplay between memory in data, sample size, dimension, and signal strength in statistical inference. In this model, an…

Statistics Theory · Mathematics 2022-10-13 Yihan Zhang , Nir Weinberger

We study the mean-median map as a dynamical system on the space of finite sets of piecewise-affine continuous functions with rational coefficients. We determine the structure of the limit function in the neighbourhood of a distinctive…

Dynamical Systems · Mathematics 2019-11-11 Jonathan Hoseana , Franco Vivaldi

Metric mean dimension is a dynamical counterpart of the box dimension in fractal geometry to characterize the topological complexity of infinite entropy systems. The classical variational principle states that topological entropy equals the…

Dynamical Systems · Mathematics 2025-12-18 Rui Yang , Xiaoyao Zhou

One of the goals of this article is to define a an unified setting adapted to the description of means (normalized integrals or invariant means) on an infinite product of measured spaces with infinite measure. We first remark that some…

Differential Geometry · Mathematics 2018-07-16 Jean-Pierre Magnot

This paper extends some results of [M5] and [M3], in particular, removing assumptions of positive lower density. We give conditions on a general family $P_{\lambda}:\mathbb{R}^{n}\to\mathbb{R}^{m}, \lambda \in \Lambda,$ of orthogonal…

Classical Analysis and ODEs · Mathematics 2023-10-12 Pertti Mattila

This note analyzes properties of the median $\nu$ of the Poisson distribution of order $k$. Given a value for the median in the interval $\nu\in[1,k]$, an equation to calculate the corresponding value of the rate parameter $\lambda$ is…

Probability · Mathematics 2023-10-24 S. R. Mane

The intermediate dimensions are a family of dimensions introduced in 2019 by Falconer, Fraser, and Kempton [arXiv:1811.06493] to interpolate between the Hausdorff dimension and the box dimension. To date, there are limited examples of…

Metric Geometry · Mathematics 2020-08-25 Justin T. Tan

Given two high-dimensional Gaussians with the same mean, we prove a lower and an upper bound for their total variation distance, which are within a constant factor of one another.

Statistics Theory · Mathematics 2023-10-24 Luc Devroye , Abbas Mehrabian , Tommy Reddad

We show that the set of numbers that are $Q$-distribution normal but not simply $Q$-ratio normal has full Hausdorff dimension. It is further shown under some conditions that countable intersections of sets of this form still have full…

Number Theory · Mathematics 2014-04-17 Bill Mance

The basic properties of the Fisher information allow to reveal the statistical meaning of classical inequalities between mean functions. The properties applied to scale mixtures of Gaussian distributions lead to a new mean function of…

Statistics Theory · Mathematics 2019-04-09 Abram M. Kagan , Paul J. Smith

A corpus of vector-embedded text documents has some empirical distribution. Given two corpora, we want to calculate a single metric of distance (e.g., Mauve, Frechet Inception) between them. We describe an abstract quality, called…

Computation and Language · Computer Science 2023-10-24 Samuel Ackerman , George Kour , Eitan Farchi

We provide an implementation to compute the flat metric in any dimension. The flat metric, also called dual bounded Lipschitz distance, generalizes the well-known Wasserstein distance $W_1$ to the case that the distributions are of unequal…

Machine Learning · Computer Science 2025-06-17 Henri Schmidt , Christian Düll

We consider Schmidt's game on the space of compact subsets of a given metric space equipped with the Hausdorff metric, and the space of continuous functions equipped with the supremum norm. We are interested in determining the generic…

Metric Geometry · Mathematics 2021-03-26 Ábel Farkas , Jonathan M. Fraser , Erez Nesharim , David Simmons

Non-autonomous iterated function systems are a generalization of iterated function systems. If the contractions in the system are conformal mappings, it is called a non-autonomous conformal iterated function system, and its attractor is…

Dynamical Systems · Mathematics 2025-12-23 Junjie Miao , Tianrui Wang
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