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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

Generative network models play an important role in algorithm development, scaling studies, network analysis, and realistic system benchmarks for graph data sets. A complex network model gaining considerable popularity builds random…

Data Structures and Algorithms · Computer Science 2018-02-12 Moritz von Looz , Henning Meyerhenke

We give a nearly optimal sublinear-time algorithm for approximating the size of a minimum vertex cover in a graph G. The algorithm may query the degree deg(v) of any vertex v of its choice, and for each 1 <= i <= deg(v), it may ask for the…

Data Structures and Algorithms · Computer Science 2011-10-06 Krzysztof Onak , Dana Ron , Michal Rosen , Ronitt Rubinfeld

The maximum genus $\gamma_M(G)$ of a graph G is the largest genus of an orientable surface into which G has a cellular embedding. Combinatorially, it coincides with the maximum number of disjoint pairs of adjacent edges of G whose removal…

Combinatorics · Mathematics 2015-01-30 Michal Kotrbcik , Martin Skoviera

In this paper we provide a parallel algorithm that given any $n$-node $m$-edge directed graph and source vertex $s$ computes all vertices reachable from $s$ with $\tilde{O}(m)$ work and $n^{1/2 + o(1)}$ depth with high probability in $n$ .…

Data Structures and Algorithms · Computer Science 2019-12-09 Arun Jambulapati , Yang P. Liu , Aaron Sidford

Graphs are widely used for describing systems made up of many interacting components and for understanding the structure of their interactions. Various statistical models exist, which describe this structure as the result of a combination…

Methodology · Statistics 2021-06-28 Louis Duvivier , Rémy Cazabet , Céline Robardet

This paper deals with the problem of finding a collection of vertex-disjoint paths in a given graph G=(V,E) such that each path has at least four vertices and the total number of vertices in these paths is maximized. The problem is NP-hard…

Data Structures and Algorithms · Computer Science 2023-04-26 Mingyang Gong , Zhi-Zhong Chen , Guohui Lin , Zhaohui Zhan

Given a road network modelled as a planar straight-line graph $G=(V,E)$ with $|V|=n$, let $(u,v)\in V\times V$, the shortest path (distance) between $u,v$ is denoted as $\delta_G(u,v)$. Let $\delta(G)=\max_{(u,v)}\delta_G(u,v)$, for…

Computational Geometry · Computer Science 2024-05-01 Zhidan Feng , Henning Fernau , Binhai Zhu

The problem of identifying important players in a given network is of pivotal importance for viral marketing, public health management, network security and various other fields of social network analysis. In this work we find the most…

Discrete Mathematics · Computer Science 2017-11-03 Juvaria Tariq , Muhammad Ahmad , Imdadullah Khan , Mudassir Shabbir

We introduce a new percolation model to describe and analyze the spread of an epidemic on a general directed and locally finite graph. We assign a two-dimensional random weight vector to each vertex of the graph in such a way that the…

Probability · Mathematics 2010-03-30 Ronald Meester , Pieter Trapman

Given any two vertices u, v of a random geometric graph, denote by d_E(u,v) their Euclidean distance and by d_G(u,v) their graph distance. The problem of finding upper bounds on d_G(u,v) in terms of d_E(u,v) has received a lot of attention…

Discrete Mathematics · Computer Science 2014-04-21 Josep Díaz , Dieter Mitsche , Guillem Perarnau , Xavier Pérez-Giménez

Sampling technique has become one of the recent research focuses in the graph-related fields. Most of the existing graph sampling algorithms tend to sample the high degree or low degree nodes in the complex networks because of the…

Social and Information Networks · Computer Science 2018-02-02 Junpeng Zhu , Hui Li , Mei Chen , Zhenyu Dai , Ming Zhu

The notions of bounded expansion and nowhere denseness not only offer robust and general definitions of uniform sparseness of graphs, they also describe the tractability boundary for several important algorithmic questions. In this paper we…

Discrete Mathematics · Computer Science 2019-09-25 Wojciech Nadara , Marcin Pilipczuk , Roman Rabinovich , Felix Reidl , Sebastian Siebertz

An instance of the Connected Maximum Cut problem consists of an undirected graph G = (V, E) and the goal is to find a subset of vertices S $\subseteq$ V that maximizes the number of edges in the cut \delta(S) such that the induced graph…

Data Structures and Algorithms · Computer Science 2015-07-03 MohammadTaghi Hajiaghayi , Guy Kortsarz , Robert MacDavid , Manish Purohit , Kanthi Sarpatwar

Network reliability is a well-studied problem that requires to measure the probability that a target node is reachable from a source node in a probabilistic (or uncertain) graph, i.e., a graph where every edge is assigned a probability of…

Social and Information Networks · Computer Science 2018-05-01 Arijit Khan , Francesco Bonchi , Francesco Gullo , Andreas Nufer

We describe approximation algorithms in Linial's classic LOCAL model of distributed computing to find maximum-weight matchings in a hypergraph of rank $r$. Our main result is a deterministic algorithm to generate a matching which is an…

Data Structures and Algorithms · Computer Science 2023-10-13 David G. Harris

Let $X_1,X_2,...$ be an infinite sequence of i.i.d. random vectors distributed exponentially with parameter $\lam .$ For each $y$ and $n\geq 1,$ form a graph $G_n(y)$ with vertex set $V_n = \{X_1,...,X_n\},$ two vertices are connected if…

Probability · Mathematics 2007-05-23 Bhupendra Gupta

We present a novel framework based on optimal transport for the challenging problem of comparing graphs. Specifically, we exploit the probabilistic distribution of smooth graph signals defined with respect to the graph topology. This allows…

Machine Learning · Computer Science 2019-12-09 Hermina Petric Maretic , Mireille EL Gheche , Giovanni Chierchia , Pascal Frossard

Distances in a network capture relations between nodes and are the basis of centrality, similarity, and influence measures. Often, however, the relevance of a node $u$ to a node $v$ is more precisely measured not by the magnitude of the…

Social and Information Networks · Computer Science 2016-02-25 Eliav Buchnik , Edith Cohen

A temporal graph is a graph in which edges are assigned a time label. Two nodes u and v of a temporal graph are connected one to the other if there exists a path from u to v with increasing edge time labels. We consider the problem of…

Data Structures and Algorithms · Computer Science 2023-04-04 Alkida Balliu , Filippo Brunelli , Pierluigi Crescenzi , Dennis Olivetti , Laurent Viennot