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We investigate the joint distribution of the vertex degrees in three models of random bipartite graphs. Namely, we can choose each edge with a specified probability, choose a specified number of edges, or specify the vertex degrees in one…

Combinatorics · Mathematics 2022-12-22 Brendan D. McKay , Fiona Skerman

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

We consider the Erdos-Renyi random graph G(n,p) inside the critical window, that is when p=1/n+ lambda*n^{-4/3}, for some fixed lambda in R. Then, as a metric space with the graph distance rescaled by n^{-1/3}, the sequence of connected…

Probability · Mathematics 2009-05-06 Louigi Addario-Berry , Nicolas Broutin , Christina Goldschmidt

We consider the infinite directed graph with vertices the set of integers ...,-2,-1,0,1,2,... . Let v be a random variable taking either finite values or value "minus infinity". Consider random weights v(j,k), indexed by pairs (j,k) of…

Probability · Mathematics 2021-10-01 S. Foss , T. Konstantopoulos , A. Logachev , A. Mogulski

We consider approximations for computing minimum weighted cuts in directed graphs. We consider both rooted and global minimum cuts, and both edge-cuts and vertex-cuts. For these problems we give randomized Monte Carlo algorithms that…

Data Structures and Algorithms · Computer Science 2021-04-15 Kent Quanrud

The use of data-random graphs in statistical testing of spatial patterns is introduced recently. In this approach, a random directed graph is constructed from the data using the relative positions of the points from various classes.…

Statistics Theory · Mathematics 2009-07-01 Elvan Ceyhan

We consider classes of pseudo-random graphs on $n$ vertices for which the degree of every vertex and the co-degree between every pair of vertices are in the intervals $(np - Cn^\delta,np+Cn^\delta)$ and $(np^2- C n^\delta, np^2 +C…

Probability · Mathematics 2016-10-13 Anirban Basak , Shankar Bhamidi , Suman Chakraborty , Andrew Nobel

Local convergence of bounded degree graphs was introduced by Benjamini and Schramm. This result was extended further by Lyons to bounded average degree graphs. In this paper, we study the convergence of a random tree sequence where the…

Probability · Mathematics 2014-02-04 Attila Deák

We study the distances of edges within cliques in a soft random geometric graph on a torus, where the vertices are points of a homogeneous Poisson point process, and far-away points are less likely to be connected than nearby points. We…

Probability · Mathematics 2024-07-17 Ercan Sönmez , Clara Stegehuis

We study the two-player communication problem of determining whether two vertices $x, y$ are nearby in a graph $G$, with the goal of determining the graph structures that allow the problem to be solved with a constant-cost randomized…

Data Structures and Algorithms · Computer Science 2023-12-18 Louis Esperet , Nathaniel Harms , Andrey Kupavskii

In Chung-Lu random graphs, a classic model for real-world networks, each vertex is equipped with a weight drawn from a power-law distribution, and two vertices form an edge independently with probability proportional to the product of their…

Discrete Mathematics · Computer Science 2018-11-06 Karl Bringmann , Ralph Keusch , Johannes Lengler

We consider an inhomogeneous version of the Barak-Erd\H{o}s graph, i.e. a directed Er\H{o}s-R\'enyi random graph on $\{1,\ldots,n\}$ with no loop. Given $f$ a Riemann-integrable non-negative function on $[0,1]^2$ and $\gamma > 0$, we define…

Probability · Mathematics 2022-01-13 Bastien Mallein , Pavel Tesemnikov

Binomial random intersection graphs can be used as parsimonious statistical models of large and sparse networks, with one parameter for the average degree and another for transitivity, the tendency of neighbours of a node to be connected.…

Social and Information Networks · Computer Science 2018-06-26 Joona Karjalainen , Lasse Leskelä

Comparing graphs by means of optimal transport has recently gained significant attention, as the distances induced by optimal transport provide both a principled metric between graphs as well as an interpretable description of the…

Machine Learning · Computer Science 2024-03-26 James S. Nagai , Ivan G. Costa , Michael T. Schaub

We show that every directed graph $G$ with $n$ vertices and $m$ edges admits a directed acyclic graph (DAG) with $m^{1+o(1)}$ edges, called a DAG projection, that can either $(1+1/\text{polylog} (n))$-approximate distances between all pairs…

Data Structures and Algorithms · Computer Science 2026-04-07 Bernhard Haeupler , Yonggang Jiang , Thatchaphol Saranurak

In this article, we analyze the limiting eigenvalue distribution (LED) of random geometric graphs (RGGs). The RGG is constructed by uniformly distributing $n$ nodes on the $d$-dimensional torus $\mathbb{T}^d \equiv [0, 1]^d$ and connecting…

Spectral Theory · Mathematics 2019-10-22 Mounia Hamidouche , Laura Cottatellucci , Konstantin Avrachenkov

In a random linear graph, vertices are points on a line, and pairs of vertices are connected, independently, with a link probability that decreases with distance. We study the problem of reconstructing the linear embedding from the graph,…

Combinatorics · Mathematics 2020-05-25 Israel Rocha , Jeannette Janssen , Nauzer Kalyaniwalla

In this paper we obtain the density function and the distribution function of the distance between two uniformly and independently distributed random points in any right-angled triangle. The density function is derived from the chord length…

Probability · Mathematics 2012-09-18 Uwe Bäsel

We study random graphs, both $G(n,p)$ and $G(n,m)$, with random orientations on the edges. For three fixed distinct vertices s,a,b we study the correlation, in the combined probability space, of the events a -> s and s -> b. For G(n,p), we…

Probability · Mathematics 2010-06-18 Sven Erick Alm , Svante Janson , Svante Linusson

Global variational approximation methods in graphical models allow efficient approximate inference of complex posterior distributions by using a simpler model. The choice of the approximating model determines a tradeoff between the…

Artificial Intelligence · Computer Science 2013-01-14 Tal El-Hay , Nir Friedman