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Random walks on graphs are an essential primitive for many randomised algorithms and stochastic processes. It is natural to ask how much can be gained by running $k$ multiple random walks independently and in parallel. Although the cover…

Discrete Mathematics · Computer Science 2026-02-19 Nicolás Rivera , Thomas Sauerwald , John Sylvester

A set $V$ is said to be separated by subsets $V_1,\ldots,V_k$ if, for every pair of distinct elements of $V$, there is a set $V_i$ that contains exactly one of them. Imposing structural constraints on the separating subsets is often…

Combinatorics · Mathematics 2024-08-06 Lyuben Lichev , Nicolás Sanhueza-Matamala

We consider the problem of decomposing the edges of a directed graph into as few paths as possible. There is a natural lower bound for the number of paths needed in an edge decomposition of a directed graph $D$ in terms of its degree…

Combinatorics · Mathematics 2021-09-29 Alberto Espuny Díaz , Viresh Patel , Fabian Stroh

A graph generative model defines a distribution over graphs. One type of generative model is constructed by autoregressive neural networks, which sequentially add nodes and edges to generate a graph. However, the likelihood of a graph under…

Machine Learning · Statistics 2021-06-15 Xiaohui Chen , Xu Han , Jiajing Hu , Francisco J. R. Ruiz , Liping Liu

We analyze a minimal model of a growing network. At each time step, a new vertex is added; then, with probability delta, two vertices are chosen uniformly at random and joined by an undirected edge. This process is repeated for t time…

Statistical Mechanics · Physics 2009-11-07 Duncan S. Callaway , John E. Hopcroft , Jon M. Kleinberg , M. E. J. Newman , Steven H. Strogatz

We study a new algorithmic process of graph growth which starts from a single initial vertex and operates in discrete time-steps, called \emph{slots}. In every slot, the graph grows via two operations (i) vertex generation and (ii) edge…

Data Structures and Algorithms · Computer Science 2022-12-20 George B. Mertzios , Othon Michail , George Skretas , Paul G. Spirakis , Michail Theofilatos

Real networks are often dynamic. In response to it, analyses of algorithms on {\em dynamic networks} attract more and more attentions in network science and engineering. Random walks on dynamic graphs also have been investigated actively in…

Probability · Mathematics 2020-08-26 Shuji Kijima , Nobutaka Shimizu , Takeharu Shiraga

Consider a graph $G=(V,E)$ and an initial random coloring where each vertex $v \in V$ is blue with probability $P_b$ and red otherwise, independently from all other vertices. In each round, all vertices simultaneously switch their color to…

Data Structures and Algorithms · Computer Science 2017-11-21 Bernd Gärtner , Ahad N. Zehmakan

Let H = (V,E) be a k-uniform hypergraph with a vertex set V and an edge set E. Let V_p be constructed by taking every vertex in V independently with probability p. Let X be the number of edges in E that are contained in V_p. We give a…

Combinatorics · Mathematics 2009-12-22 Guy Wolfovitz

We propose and analyze a quasirandom analogue of the classical push model for disseminating information in networks ("randomized rumor spreading"). In the classical model, in each round each informed vertex chooses a neighbor at random and…

Data Structures and Algorithms · Computer Science 2015-03-17 Benjamin Doerr , Tobias Friedrich , Thomas Sauerwald

In the sufficiently sparse case, we find the probability that a uniformly random bipartite graph with given degree sequence contains no edge from a specified set of edges. This enables us to enumerate loop-free digraphs and oriented graphs…

Combinatorics · Mathematics 2026-01-09 Catherine Greenhill , Mahdieh Hasheminezhad , Isaiah Iliffe , Brendan D. McKay

The planted densest subgraph detection problem refers to the task of testing whether in a given (random) graph there is a subgraph that is unusually dense. Specifically, we observe an undirected and unweighted graph on $n$ vertices. Under…

Data Structures and Algorithms · Computer Science 2024-05-06 Wasim Huleihel , Arya Mazumdar , Soumyabrata Pal

We consider a modified random walk which uses unvisited edges whenever possible, and makes a simple random walk otherwise. We call such a walk an edge-process. We assume there is a rule A, which tells the walk which unvisited edge to use…

Data Structures and Algorithms · Computer Science 2015-03-20 Petra Berenbrink , Colin Cooper , Tom Friedetzky

We study the properties of random graphs where for each vertex a {\it neighbourhood} has been previously defined. The probability of an edge joining two vertices depends on whether the vertices are neighbours or not, as happens in Small…

Disordered Systems and Neural Networks · Physics 2009-11-10 Sebastian Risau-Gusman

In this paper, we develop a novel paradigm, namely hypergraph shift, to find robust graph modes by probabilistic voting strategy, which are semantically sound besides the self-cohesiveness requirement in forming graph modes. Unlike the…

Artificial Intelligence · Computer Science 2017-04-13 Yang Wang , Lin Wu

We study continuous time Markov processes on graphs. The notion of frequency is introduced, which serves well as a scaling factor between any Markov time of a continuous time Markov process and that of its jump chain. As an application, we…

Probability · Mathematics 2007-05-23 Jianjun Tian , Xiao-Song Lin

The isoperimetric constant of a graph $G$ on $n$ vertices, $i(G)$, is the minimum of $\frac{|\partial S|}{|S|}$, taken over all nonempty subsets $S\subset V(G)$ of size at most $n/2$, where $\partial S$ denotes the set of edges with…

Probability · Mathematics 2007-05-23 Itai Benjamini , Simi Haber , Michael Krivelevich , Eyal Lubetzky

We study stochastic graph optimization problems in a novel distributed setting. As in the standard centralized setting, a random subgraph $G^*$ of a known base graph $G$ is realized by including each edge $e$ independently with a known…

Data Structures and Algorithms · Computer Science 2026-05-21 Keren Censor-Hillel , Aditi Dudeja , George Giakkoupis

We study the 2-offer semirandom 3-uniform hypergraph model on $n$ vertices. At each step, we are presented with 2 uniformly random vertices. We choose any other vertex, thus creating a hyperedge of size 3. We show a strategy that constructs…

Combinatorics · Mathematics 2024-09-26 Michael Molloy , Pawel Pralat , Gregory B. Sorkin

We apply in this article (non rigorous) statistical mechanics methods to the problem of counting long circuits in graphs. The outcomes of this approach have two complementary flavours. On the algorithmic side, we propose an approximate…

Statistical Mechanics · Physics 2009-11-11 Enzo Marinari , Guilhem Semerjian