English
Related papers

Related papers: On the edit distance function of the random graph

200 papers

The chromatic threshold $\delta_\chi(H,p)$ of a graph $H$ with respect to the random graph $G(n,p)$ is the infimum over $d > 0$ such that the following holds with high probability: the family of $H$-free graphs $G \subset G(n,p)$ with…

Combinatorics · Mathematics 2016-08-15 Peter Allen , Julia Böttcher , Simon Griffiths , Yoshiharu Kohayakawa , Robert Morris

We study a discrete-time duplication-deletion random graph model and analyse its asymptotic degree distribution. The random graphs consists of disjoint cliques. In each time step either a new vertex is brought in with probability $0<p<1$…

Probability · Mathematics 2017-02-24 Erik Thörnblad

Random graph matching refers to recovering the underlying vertex correspondence between two random graphs with correlated edges; a prominent example is when the two random graphs are given by Erd\H{o}s-R\'{e}nyi graphs $G(n,\frac{d}{n})$.…

Machine Learning · Statistics 2020-07-21 Jian Ding , Zongming Ma , Yihong Wu , Jiaming Xu

We study a random graph model in continuous time. Each vertex is partially copied with the same rate, i.e.\ an existing vertex is copied and every edge leading to the copied vertex is copied with independent probability $p$. In addition,…

Probability · Mathematics 2024-07-02 Felix Hermann , Peter Pfaffelhuber

For a $d$-uniform random hypergraph on $n$ vertices in which hyperedges are included i.i.d.\ so that the average degree in the hypergraph is $n^{\delta+o(1)}$, the projection of such a hypergraph is a graph on the same $n$ vertices where an…

Statistics Theory · Mathematics 2026-04-03 Shuyang Gong , Zhangsong Li , Qiheng Xu

We investigate the maximum-entropy model $\mathcal{B}_{n,m,p}$ for random $n$-vertex, $m$-edge multi-hypergraphs with expected edge size $pn$. We show that the expected size of the minimization of $\mathcal{B}_{n,m,p}$, i.e., the number of…

Discrete Mathematics · Computer Science 2020-11-03 Thomas Bläsius , Tobias Friedrich , Martin Schirneck

We study hypergraph discrepancy in two closely related random models of hypergraphs on $n$ vertices and $m$ hyperedges. The first model, $\mathcal{H}_1$, is when every vertex is present in exactly $t$ randomly chosen hyperedges. The premise…

Combinatorics · Mathematics 2018-11-06 Aditya Potukuchi

Recent works of Alon-Shapira and R\"odl-Schacht have demonstrated that every hereditary property of undirected graphs or hypergraphs is testable with one-sided error; informally, this means that if a graph or hypergraph satisfies that…

Combinatorics · Mathematics 2009-05-12 Tim Austin , Terence Tao

The edge space $\mathcal{E}(G)$ of a graph $G$ is the vector space $\mathbb{F}_2^{E(G)}$ with members naturally identified with subgraphs of $G$, and the $H$-space is the subspace $\mathcal{C}_H(G)$ of $ \mathcal{E}(G)$ spanned by copies of…

Combinatorics · Mathematics 2024-10-10 Quentin Dubroff , Jeff Kahn

We show that the probability that a random graph $G\sim G(n,p)$ contains no Hamilton cycle is $(1+o(1))Pr(\delta (G) < 2)$ for all values of $p = p(n)$. We also prove an analogous result for perfect matchings.

Combinatorics · Mathematics 2019-12-20 Yahav Alon , Michael Krivelevich

Letting $\mathcal{M}$ denote the space of finite measures on $\mathbb{N}$, and $\mu_\lambda\in\mathcal{M}$ denote the Poisson distribution with parameter $\lambda$, the function $W:[0,1]^2\to\mathcal{M}$ given by \[ W(x,y)=\mu_{c\log x\log…

Combinatorics · Mathematics 2017-01-25 Ágnes Backhausz , Dávid Kunszenti-Kovács

The Graph Edit Distance (GED) is an important metric for measuring the similarity between two (labeled) graphs. It is defined as the minimum cost required to convert one graph into another through a series of (elementary) edit operations.…

Databases · Computer Science 2025-11-05 Andrea D'Ascenzo , Julian Meffert , Petra Mutzel , Fabrizio Rossi

A preferential attachment model for a growing network incorporating deletion of edges is studied and the expected asymptotic degree distribution is analyzed. At each time step $t=1,2,\ldots$, with probability $\pi_1>0$ a new vertex with one…

Physics and Society · Physics 2015-09-30 Maria Deijfen , Mathias Lindholm

We connect several notions relating the structural and dynamical properties of a graph. Among them are the topological entropy coming from the vertex shift, which is related to the spectral radius of the graph's adjacency matrix, the…

Combinatorics · Mathematics 2025-12-29 Fatihcan M. Atay , Türker Bıyıkoğlu

To each edge (i,j), i<j of the complete directed graph on the integers we assign unit weight with probability p or weight x with probability 1-p, independently from edge to edge, and give to each path weight equal to the sum of its edge…

Probability · Mathematics 2022-06-29 Sergey Foss , Takis Konstantopoulos , Artem Pyatkin

The random intersection graph model $\mathcal G(n,m,p)$ is considered. Due to substantial edge dependencies, studying even fundamental statistics such as the subgraph count is significantly more challenging than in the classical binomial…

Combinatorics · Mathematics 2025-04-01 Katarzyna Rybarczyk , Grzegorz Serafin

A path in an edge-colored graph is called a \emph{rainbow path} if all edges on it have pairwise distinct colors. For $k\geq 1$, the \emph{rainbow-$k$-connectivity} of a graph $G$, denoted $rc_k(G)$, is the minimum number of colors required…

Combinatorics · Mathematics 2012-03-06 Jing He , Hongyu Liang

For a graph $G$ and $p\in[0,1]$, we denote by $G_p$ the random sparsification of $G$ obtained by keeping each edge of $G$ independently, with probability $p$. We show that there exists a $C>0$ such that if $p\geq C(\log n)^{1/3}n^{-2/3}$…

In this paper we explore first passage percolation (FPP) on the Erd\H{o}s-R\'enyi random graph $G_n(p_n)$, where each edge is given an independent exponential edge weight with rate 1. In the sparse regime, i.e., when $np_n\to \lambda>1,$ we…

Probability · Mathematics 2010-05-25 Shankar Bhamidi , Remco van der Hofstad , Gerard Hooghiemstra

Graph edit distance (GED) is a powerful and flexible graph matching paradigm that can be used to address different tasks in structural pattern recognition, machine learning, and data mining. In this paper, some new binary linear programming…

Data Structures and Algorithms · Computer Science 2015-05-22 Julien Lerouge , Zeina Abu-Aisheh , Romain Raveaux , Pierre Héroux , Sébastien Adam