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Consider the inhomogeneous Erd\H{o}s-R\'enyi random graph (ERRG) on $n$ vertices for which each pair $i,j\in\{1,\ldots,n\}$, $i\neq j$ is connected independently by an edge with probability $r_n(\frac{i-1}{n},\frac{j-1}{n})$, where…

Probability · Mathematics 2022-08-23 Maarten Markering

We introduce a model for a growing random graph based on simultaneous reproduction of the vertices. The model can be thought of as a generalisation of the reproducing graphs of Southwell and Cannings and Bonato et al to allow for a random…

Probability · Mathematics 2011-04-20 Jonathan Jordan

We show that almost surely the rank of the adjacency matrix of the Erd\"os-R\'enyi random graph $G(n,p)$ equals the number of non-isolated vertices for any $c\ln n/n<p<1/2$, where $c$ is an arbitrary positive constant larger than 1/2. In…

Probability · Mathematics 2007-05-23 Kevin P. Costello , Van H. Vu

Random sequential addition (RSA) time-dependent packing process, in which congruent hard hyperspheres are randomly and sequentially placed into a system without interparticle overlap, is a useful packing model to study disorder in high…

Statistical Mechanics · Physics 2014-02-21 G. Zhang , S. Torquato

We study the graph alignment problem over two independent Erd\H{o}s-R\'enyi graphs on $n$ vertices, with edge density $p$ falling into two regimes separated by the critical window around $p_c=\sqrt{\log n/n}$. Our result reveals an…

Probability · Mathematics 2025-03-27 Hang Du , Shuyang Gong , Rundong Huang

Starting with the large deviation principle (LDP) for the Erd\H{o}s-R\'enyi binomial random graph $\mathcal{G}(n,p)$ (edge indicators are i.i.d.), due to Chatterjee and Varadhan (2011), we derive the LDP for the uniform random graph…

Probability · Mathematics 2018-05-01 Amir Dembo , Eyal Lubetzky

In this article, we derive Stein's method for approximating a spatial random graph by a generalised random geometric graph, which has vertices given by a finite Gibbs point process and edges based on a general connection function. Our main…

Probability · Mathematics 2024-11-06 Dominic Schuhmacher , Leoni Carla Wirth

For the classical maximum coverage problem, the greedy algorithm achieves a worst-case $1-1/e$ approximation, which is optimal unless $\text{P} = \text{NP}$. The notion of coverage appears in a wide range of optimization tasks, where…

Data Structures and Algorithms · Computer Science 2026-04-29 Eric Balkanski , Jason Chatzitheodorou , Flore Sentenac

We study logical limit laws for uniform attachment random graphs. In this random graph model, vertices and edges are introduced recursively: at time $n+1$, the vertex $n+1$ is introduced together with $m$ edges joining the new vertex with…

Probability · Mathematics 2022-01-03 Yury Malyshkin , Maksim Zhukovskii

Graph coarsening aims to diminish the size of a graph to lighten its memory footprint, and has numerous applications in graph signal processing and machine learning. It is usually defined using a reduction matrix and a lifting matrix,…

Machine Learning · Computer Science 2026-01-29 Antonin Joly , Nicolas Keriven , Aline Roumy

We present results on the concentration properties of the spectral norm $\|A_p\|$ of the adjacency matrix $A_p$ of an Erd\H{o}s-R\'enyi random graph $G(n,p)$. First we consider the Erd\H{o}s-R\'enyi random graph process and prove that…

Probability · Mathematics 2018-11-21 Gábor Lugosi , Shahar Mendelson , Nikita Zhivotovskiy

Relative entropy coding (REC) algorithms encode a sample from a target distribution $Q$ using a proposal distribution $P$ using as few bits as possible. Unlike entropy coding, REC does not assume discrete distributions or require…

Information Theory · Computer Science 2023-09-28 Gergely Flamich , Stratis Markou , Jose Miguel Hernandez Lobato

We use random matrix theory to study the spectrum of random geometric graphs, a fundamental model of spatial networks. Considering ensembles of random geometric graphs we look at short range correlations in the level spacings of the…

Physics and Society · Physics 2017-06-08 Carl P. Dettmann , Orestis Georgiou , Georgie Knight

The problems of detecting and recovering planted structures/subgraphs in Erd\H{o}s-R\'{e}nyi random graphs, have received significant attention over the past three decades, leading to many exciting results and mathematical techniques.…

Statistics Theory · Mathematics 2025-05-20 Dor Elimelech , Wasim Huleihel

We compute an asymptotic expansion in $1/c$ of the limit in $n$ of the empirical spectral measure of the adjacency matrix of an Erd\H{o}s-R\'enyi random graph with $n$ vertices and parameter $c/n$. We present two different methods, one of…

Probability · Mathematics 2017-01-05 Nathanael Enriquez , Laurent Menard

In this paper we analyze the practical implications of Szemer\'edi's regularity lemma in the preservation of metric information contained in large graphs. To this end, we present a heuristic algorithm to find regular partitions. Our…

Data Structures and Algorithms · Computer Science 2017-03-22 Marco Fiorucci , Alessandro Torcinovich , Manuel Curado , Francisco Escolano , Marcello Pelillo

The Aldous--Broder algorithm provides a way of sampling a uniformly random spanning tree for finite connected graphs using simple random walk. Namely, start a simple random walk on a connected graph and stop at the cover time. The tree…

Probability · Mathematics 2021-03-29 Yiping Hu , Russell Lyons , Pengfei Tang

Random sequential adsorption (RSA) of various two dimensional objects is studied in order to find a shape which maximizes the saturated packing fraction. This investigation was begun in our previous paper [Cie\'sla et al., Phys. Chem. Chem.…

Materials Science · Physics 2016-08-02 Michał Cieśla , Grzegorz Pająk , Robert M. Ziff

We study which property testing and sublinear time algorithms can be transformed into graph streaming algorithms for random order streams. Our main result is that for bounded degree graphs, any property that is constant-query testable in…

Data Structures and Algorithms · Computer Science 2017-07-25 Morteza Monemizadeh , S. Muthukrishnan , Pan Peng , Christian Sohler

The frame algorithm uses a simple recursive formula to approximate an unknown vector from its frame coefficients. This note introduces an adaptive version of the frame algorithm that maximizes the error reduction between steps in terms of…

Functional Analysis · Mathematics 2025-06-24 Brody Dylan Johnson