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We consider sparse random intersection graphs with the property that the clustering coefficient does not vanish as the number of nodes tends to infinity. We find explicit asymptotic expressions for the correlation coefficient of degrees of…

Probability · Mathematics 2019-08-24 Mindaugas Bloznelis , Jerzy Jaworski , Valentas Kurauskas

The reconfiguration graph $\mathcal{C}_k(G)$ for the $k$-colourings of a graph $G$ has a vertex for each proper $k$-colouring of $G$, and two vertices of $\mathcal{C}_k(G)$ are adjacent precisely when those $k$-colourings differ on a single…

Combinatorics · Mathematics 2023-10-03 Stijn Cambie , Wouter Cames van Batenburg , Daniel W. Cranston

Testing for independence between graphs is a problem that arises naturally in social network analysis and neuroscience. In this paper, we address independence testing for inhomogeneous Erd\H{o}s-R\'{e}nyi random graphs on the same vertex…

Methodology · Statistics 2023-04-19 Yukun Song , Carey E. Priebe , Minh Tang

Modeling heterogeneous correlated time series requires the ability to learn hidden dynamic relationships between component time series with possibly varying periodicities and generative processes. To address this challenge, we formulate and…

Methodology · Statistics 2025-12-02 Jeshwanth Mohan , Bharath Ramsundar , Sandya Subramanian

In this paper we study the component structure of random graphs with independence between the edges. Under mild assumptions, we determine whether there is a giant component, and find its asymptotic size when it exists. We assume that the…

Probability · Mathematics 2010-06-29 Bela Bollobas , Svante Janson , Oliver Riordan

We study the expected adjacency matrix of a uniformly random multigraph with fixed degree sequence $\mathbf{d} \in \mathbb{Z}_+^n$. This matrix arises in a variety of analyses of networked data sets, including modularity-maximization and…

Social and Information Networks · Computer Science 2020-02-10 Philip S. Chodrow

We prove that for $k+1\geq 3$ and $c>(k+1)/2$ w.h.p. the random graph on $n$ vertices, $cn$ edges and minimum degree $k+1$ contains a (near) perfect $k$-matching. As an immediate consequence we get that w.h.p. the $(k+1)$-core of $G_{n,p}$,…

Combinatorics · Mathematics 2021-07-09 Michael Anastos

The $\lambda$-core vertices of a graph correspond to the non-zero entries of some eigenvector of $\lambda$ for a universal adjacency matrix $\mathbf{U}$ of the graph. We define a partition of the vertex set $V$ based on the $\lambda$-core…

Combinatorics · Mathematics 2021-03-02 Xandru Mifsud

This paper presents a graph signal processing algorithm to uncover the intrinsic low-rank components and the underlying graph of a high-dimensional, graph-smooth and grossly-corrupted dataset. In our problem formulation, we assume that the…

Image and Video Processing · Electrical Eng. & Systems 2018-01-09 Rui Liu , Hossein Nejati , Ngai-Man Cheung

A random intersection graph is constructed by independently assigning a subset of a given set of objects $W,$ to each vertex of the vertex set $V$ of a simple graph $G.$ There is an edge between two vertices of $V,$ iff their respective…

Probability · Mathematics 2008-09-09 Bhupendra Gupta

Recent research has shown growing interest in modeling hypergraphs, which capture polyadic interactions among entities beyond traditional dyadic relations. However, most existing methodologies for hypergraphs face significant limitations,…

Methodology · Statistics 2025-11-04 Shihao Wu , Gongjun Xu , Ji Zhu

We evaluate the particular performance of different quantum machine learning networks on a graph classification task. Quantum circuits with varying internal symmetry that completely, partially and not at all confer to the symmetry of the…

A $k$-proper edge-coloring of a graph G is called adjacent vertex-distinguishing if any two adjacent vertices are distinguished by the set of colors appearing in the edges incident to each vertex. The smallest value $k$ for which $G$ admits…

Discrete Mathematics · Computer Science 2022-01-05 Sylvain Gravier , Hippolyte Signargout , Souad Slimani

In this paper, we investigate the problem of (k,r)-core which intends to find cohesive subgraphs on social networks considering both user engagement and similarity perspectives. In particular, we adopt the popular concept of k-core to…

Social and Information Networks · Computer Science 2016-11-11 Fan Zhang , Ying Zhang , Lu Qin , Wenjie Zhang , Xuemin Lin

We introduce a random hypergraph model for core-periphery structure. By leveraging our model's sufficient statistics, we develop a novel statistical inference algorithm that is able to scale to large hypergraphs with runtime that is…

Social and Information Networks · Computer Science 2022-06-03 Marios Papachristou , Jon Kleinberg

In this paper we consider alignment of sparse graphs, for which we introduce the Neighborhood Tree Matching Algorithm (NTMA). For correlated Erd\H{o}s-R\'{e}nyi random graphs, we prove that the algorithm returns -- in polynomial time -- a…

Data Structures and Algorithms · Computer Science 2020-11-02 Luca Ganassali , Laurent Massoulié

We revisit the classical hard-core model, also known as independent set and dual to vertex cover problem, where one puts particles with a first-neighbor hard-core repulsion on the vertices of a random graph. Although the case of random…

Disordered Systems and Neural Networks · Physics 2013-12-17 Jean Barbier , Florent Krzakala , Lenka Zdeborová , Pan Zhang

The $K$-core of a graph is the unique maximum subgraph within which each vertex connects to $K$ or more other vertices. The optimal $K$-core attack problem asks to delete the minimum number of vertices from the $K$-core to induce its…

Disordered Systems and Neural Networks · Physics 2024-06-17 Jianwen Zhou , Hai-Jun Zhou

Motivated by various data science applications including de-anonymizing user identities in social networks, we consider the graph alignment problem, where the goal is to identify the vertex/user correspondence between two correlated graphs.…

Information Theory · Computer Science 2024-03-13 Ning Zhang , Ziao Wang , Weina Wang , Lele Wang

For two unlabeled graphs $G_1,G_2$ independently sub-sampled from an Erd\H{o}s-R\'enyi graph $\mathbf G(n,p)$ by keeping each edge with probability $s$, we aim to recover \emph{as many as possible} of the corresponding vertex pairs. We…

Probability · Mathematics 2025-02-18 Hang Du
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