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Let n points be placed independently in d-dimensional space according to the densities $f(x) = A_d e^{-\lambda \|x\|^{\alpha}}, \lambda > 0, x \in \Re^d, d \geq 2.$ Let $d_n$ be the longest edge length for the nearest neighbor graph on…

Probability · Mathematics 2009-05-30 Bhupendra Gupta , Srikanth K. Iyer

Consider a weighted or unweighted k-nearest neighbor graph that has been built on n data points drawn randomly according to some density p on R^d. We study the convergence of the shortest path distance in such graphs as the sample size…

Machine Learning · Computer Science 2012-07-10 Morteza Alamgir , Ulrike von Luxburg

Consider the geometric graph on $n$ independent uniform random points in a connected compact region $A$ of ${\bf R}^d, d \geq 2$, with $C^2$ boundary, or in the unit square, with distance parameter $r_n$. Let $K_n$ be the number of…

Probability · Mathematics 2026-04-09 Mathew D. Penrose , Xiaochuan Yang

We numerically investigate the robustness of networks with degree-degree correlations between nodes separated by distance $l=2$ in terms of shortest path length. The degree-degree correlation between the $l$-th nearest neighbors can be…

Physics and Society · Physics 2024-12-04 Yuka Fujiki , Stefan Junk

A random geometric graph, $G(n,r)$, is formed by choosing $n$ points independently and uniformly at random in a unit square; two points are connected by a straight-line edge if they are at Euclidean distance at most $r$. For a given…

Discrete Mathematics · Computer Science 2018-10-01 Ahmad Biniaz , Evangelos Kranakis , Anil Maheshwari , Michiel Smid

The cortex is a very large network characterized by a complex connectivity including at least two scales: a microscopic scale at which the interconnections are non-specific and very dense, while macroscopic connectivity patterns connecting…

Neurons and Cognition · Quantitative Biology 2015-06-17 Jonathan Touboul

Let $X_1,\dots,X_n$ be independent centered random vectors in $\mathbb{R}^d$. This paper shows that, even when $d$ may grow with $n$, the probability $P(n^{-1/2}\sum_{i=1}^nX_i\in A)$ can be approximated by its Gaussian analog uniformly in…

Statistics Theory · Mathematics 2022-03-08 Yuta Koike

Let $G$ be a finite, simple connected graph. The average distance of a vertex $v$ of $G$ is the arithmetic mean of the distances from $v$ to all other vertices of $G$. The remoteness $\rho(G)$ of $G$ is the maximum of the average distances…

Combinatorics · Mathematics 2024-05-27 Peter Dankelmann , Sonwabile Mafunda , Sufiyan Mallu

We study the component structure of the random graph $G=G_{n,m,d}$. Here $d=O(1)$ and $G$ is sampled uniformly from ${\mathcal G}_{n,m,d}$, the set of graphs with vertex set $[n]$, $m$ edges and maximum degree at most $d$. If $m=\mu n/2$…

Combinatorics · Mathematics 2021-06-04 Alan Frieze , Tomasz Tkocz

We consider a random geometric hypergraph model based on an underlying bipartite graph. Nodes and hyperedges are sampled uniformly in a domain, and a node is assigned to those hyperedges that lie with a certain radius. From a modelling…

Probability · Mathematics 2023-09-19 Henry-Louis de Kergorlay , Desmond J. Higham

Random K-out graphs are used in several applications including modeling by sensor networks secured by the random pairwise key predistribution scheme, and payment channel networks. The random K-out graph with $n$ nodes is constructed as…

Information Theory · Computer Science 2022-10-12 Mansi Sood , Osman Yagan

The second-largest eigenvalue and second-smallest Laplacian eigenvalue of a graph are measures of its connectivity. These eigenvalues can be used to analyze the robustness, resilience, and synchronizability of networks, and are related to…

Combinatorics · Mathematics 2018-07-20 Aida Abiad , Boris Brimkov , Xavier Martinez-Rivera , O Suil , Jingmei Zhang

We analyse graphs in which each vertex is assigned random coordinates in a geometric space of arbitrary dimensionality and only edges between adjacent points are present. The critical connectivity is found numerically by examining the size…

Statistical Mechanics · Physics 2009-11-07 Jesper Dall , Michael Christensen

The probabilistic graphs framework models the uncertainty inherent in real-world domains by means of probabilistic edges whose value quantifies the likelihood of the edge existence or the strength of the link it represents. The goal of this…

Artificial Intelligence · Computer Science 2012-05-25 Claudio Taranto , Nicola Di Mauro , Floriana Esposito

The threshold network model is a type of finite random graphs. In this paper, we introduce a generalized threshold network model. A pair of vertices with random weights is connected by an edge when real-valued functions of the pair of…

Probability · Mathematics 2010-10-12 Yusuke Ide , Norio Konno , Naoki Masuda

We consider the $(1+\epsilon)$-approximate nearest neighbor search problem: given a set $X$ of $n$ points in a $d$-dimensional space, build a data structure that, given any query point $y$, finds a point $x \in X$ whose distance to $y$ is…

Data Structures and Algorithms · Computer Science 2018-07-03 Piotr Indyk , Tal Wagner

We study the connectivity of random subgraphs of the $d$-dimensional Hamming graph $H(d, n)$, which is the Cartesian product of $d$ complete graphs on $n$ vertices. We sample the random subgraph with an i.i.d.\ Bernoulli bond percolation on…

Probability · Mathematics 2016-03-01 Lorenzo Federico , Remco van der Hofstad , Tim Hulshof

Let $G$ be a graph with a vertex set $V$. The graph $G$ is path-proximinal if there are a semimetric $d \colon V \times V \to [0, \infty[$ and disjoint proximinal subsets of the semimetric space $(V, d)$ such that $V = A \cup B$, and…

General Topology · Mathematics 2023-03-07 Karim Chaira , Oleksiy Dovgoshey

Large real-life complex networks are often modeled by various random graph constructions and hundreds of further references therein. In many cases it is not at all clear how the modeling strength of differently generated random graph model…

Data Structures and Algorithms · Computer Science 2020-09-01 András Faragó , Rupei Xu

This paper considers the asymptotic distribution of the longest edge of the minimal spanning tree and nearest neighbor graph on X_1,...,X_{N_n} where X_1,X_2,... are i.i.d. in \Re^2 with distribution F and N_n is independent of the X_i and…

Probability · Mathematics 2007-05-23 Tailen Hsing , Holger Rootzen
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