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In this paper we develop an algebraic theory to study the problem of finding the minimum distance point from an algebraic variety with respect to the Hermitian distance function. The theory generalizes the Euclidean Distance degree…

Algebraic Geometry · Mathematics 2025-10-23 Davide Furchì

Almost all statistical and machine learning methods in analyzing brain networks rely on distances and loss functions, which are mostly Euclidean or matrix norms. The Euclidean or matrix distances may fail to capture underlying subtle…

Computational Geometry · Computer Science 2021-02-18 Moo K. Chung , Alexander Smith , Gary Shiu

When we represent a network of sensors in Euclidean space by a graph, there are two distances between any two nodes that we may consider. One of them is the Euclidean distance. The other is the distance between the two nodes in the graph,…

Networking and Internet Architecture · Computer Science 2009-06-10 Rodrigo S. C. Leao , Valmir C. Barbosa

We study algorithmic problems on subsets of Euclidean space of low fractal dimension. These spaces are the subject of intensive study in various branches of mathematics, including geometry, topology, and measure theory. There are several…

Data Structures and Algorithms · Computer Science 2017-03-29 Anastasios Sidiropoulos , Vijay Sridhar

We study the Euclidean Distance degree of algebraic neural network models from the perspective of algebraic geometry. Focusing on shallow networks with two neurons, quadratic activation, and scalar output, we identify the associated…

Algebraic Geometry · Mathematics 2026-01-01 Giacomo Graziani

For non-empty sets X we define notions of distance and pseudo metric with values in a partially ordered set that has a smallest element $\theta $. If $h_X$ is a distance in $X$ (respectively, a pseudo metric in $X$), then the pair $(X,h_X)$…

Functional Analysis · Mathematics 2025-03-18 Vladyslav Babenko , Vira Babenko , Oleg Kovalenko

Spatial association and heterogeneity are two critical areas in the research about spatial analysis, geography, statistics and so on. Though large amounts of outstanding methods has been proposed and studied, there are few of them tend to…

Econometrics · Economics 2018-03-26 Zihao Yuan

We study a new class of distances between Radon measures similar to those studied in a recent paper of Dolbeault-Nazaret-Savar\'e [DNS]. These distances (more correctly pseudo-distances because can assume the value $+\infty$) are defined…

Functional Analysis · Mathematics 2009-09-15 Stefano Lisini , Antonio Marigonda

We consider the $L^p$ Hardy inequality involving the distance to the boundary for a domain in the $n$-dimensional Euclidean space. We study the dependence on $p$ of the corresponding best constant and we prove monotonicity, continuity and…

Analysis of PDEs · Mathematics 2015-10-27 Gerassimos Barbatis , Pier Domenico Lamberti

We give a characterization of harmonic and subharmonic functions in terms of their mean values in balls and on spheres. This includes the converse of an inequality of Beardon's for subharmonic functions. We also obtain integral inequalities…

Analysis of PDEs · Mathematics 2007-05-23 Pedro Freitas , Joao Palhoto Matos

We prove a series of results on the size of distance sets corresponding to sets in the Euclidean space. These distances are generated by bounded convex sets and the results depend explicitly on the geometry of these sets. We also use a…

Classical Analysis and ODEs · Mathematics 2007-05-23 A. Iosevich , I. Laba

How to evaluate the importance of nodes is essential in research of complex network. There are many methods proposed for solving this problem, but they still have room to be improved. In this paper, a new approach called local volume…

Social and Information Networks · Computer Science 2022-03-28 Hanwen Li , Qiuyan Shang , Fangzheng Duan , Yong Deng

Contraction analysis considers the distance between two adjacent trajectories. If this distance is contracting, then trajectories have the same long-term behavior. The main advantage of this analysis is that it is independent of the…

Dynamical Systems · Mathematics 2022-03-04 Peter Giesl , Sigurdur Hafstein , Christoph Kawan

The cognitive framework of conceptual spaces [3] provides geometric means for representing knowledge. A conceptual space is a high-dimensional space whose dimensions are partitioned into so-called domains. Within each domain, the Euclidean…

Artificial Intelligence · Computer Science 2017-09-25 Lucas Bechberger

The concept of $n$-distance was recently introduced to generalize the classical definition of distance to functions of $n$ arguments. In this paper we investigate this concept through a number of examples based on certain geometrical…

Metric Geometry · Mathematics 2023-02-22 Gergely Kiss , Jean-Luc Marichal

The dimension free Harnack inequality is established for the distribution dependent stochastic Hamiltonian system, where the drift is Lipschitz continuous in the measure variable under the distance induced by the H\"{o}lder-Dini continuous…

Probability · Mathematics 2022-12-29 Xing Huang , Xiaochen Ma

The connection between several hyperbolic type metrics is studied in subdomains of the Euclidean space. In particular, a new metric is introduced and compared to the distance ratio metric.

Metric Geometry · Mathematics 2018-01-29 Oleksiy Dovgoshey , Parisa Hariri , Matti Vuorinen

This paper is devoted to Hardy type inequalities with remainders for compactly supported smooth functions on open sets in the Euclidean space. We establish new inequalities with weight functions depending on the distance function to the…

Functional Analysis · Mathematics 2020-03-20 Makarov R. V. , Nasibullin R. G

In a domain of the Euclidean space, we estimate from below the distance to the boundary of global maximum points of solutions of elliptic and parabolic equations with homogeneous Dirichlet boundary values. As reference cases, we first…

Analysis of PDEs · Mathematics 2020-06-15 Rolando Magnanini , Giorgio Poggesi

This paper considers metric spaces where distances between a pair of nodes are represented by distance intervals. The goal is to study methods for the determination of hierarchical clusters, i.e., a family of nested partitions indexed by a…

Social and Information Networks · Computer Science 2016-10-17 Weiyu Huang , Alejandro Ribeiro