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We study the joint components in a random `double graph' that is obtained by superposing red and blue binomial random graphs on $n$~vertices. A joint component is a maximal set of vertices, which contains both a red and a blue spanning…

Combinatorics · Mathematics 2021-02-08 Mark Jerrum , Tamás Makai

We consider the two-star model, a family of exponential random graphs indexed by two real parameters, $h$ and $\alpha$, that rule respectively the total number of edges and the mutual dependence between them. Borrowing tools from…

Probability · Mathematics 2023-01-31 Alessandra Bianchi , Francesca Collet , Elena Magnanini

In this paper, matching pairs of random graphs under the community structure model is considered. The problem emerges naturally in various applications such as privacy, image processing and DNA sequencing. A pair of randomly generated…

Cryptography and Security · Computer Science 2018-11-01 F. Shirani , S. Garg , E. Erkip

In this article we show the duality between tensor networks and undirected graphical models with discrete variables. We study tensor networks on hypergraphs, which we call tensor hypernetworks. We show that the tensor hypernetwork on a…

Statistics Theory · Mathematics 2017-10-05 Elina Robeva , Anna Seigal

In the classical Erd\"os-R\'enyi random graph G(n,p) there are n vertices and each of the possible edges is independently present with probability p. The random graph G(n,p) is homogeneous in the sense that all vertices have the same…

Combinatorics · Mathematics 2016-02-10 Mihyun Kang , Angelica Pachón , Pablo M. Rodriguez

We present a new notion of probabilistic duality for random variables involving mixture distributions. Using this notion, we show how to implement a highly-parallelizable Gibbs sampler for weakly coupled discrete pairwise graphical models…

Machine Learning · Computer Science 2016-11-23 Lars Mescheder , Sebastian Nowozin , Andreas Geiger

Two-sample tests for multivariate data and non-Euclidean data are widely used in many fields. Parametric tests are mostly restrained to certain types of data that meets the assumptions of the parametric models. In this paper, we study a…

Methodology · Statistics 2018-05-01 Hao Chen , Xu Chen , Yi Su

This Letter introduces a generalization of known duplication-divergence models for growing random graphs. This general duplication-divergence model includes a new coupled divergence asymmetry rate, which allows to obtain the structure of…

Statistical Mechanics · Physics 2024-12-04 Dario Borrelli

A graph is diameter-2-critical if its diameter is 2 but the removal of any edge increases the diameter. A well-studied conjecture, known as the Murty-Simon conjecture, states that any diameter-2-critical graph of order n has at most…

Combinatorics · Mathematics 2026-04-17 Antoine Dailly , Florent Foucaud , Adriana Hansberg

The exponential family of random graphs is one of the most promising class of network models. Dependence between the random edges is defined through certain finite subgraphs, analogous to the use of potential energy to provide dependence…

Mathematical Physics · Physics 2015-06-11 Mei Yin

We prove a general theorem on cutoffs for symmetric exclusion and interchange processes on finite graphs $G_N=(V_N,E_N)$, under the assumption that either the graphs converge geometrically and spectrally to a compact metric measure space,…

Probability · Mathematics 2020-12-24 Joe P. Chen , Rodrigo Marinho

What does an Erdos-Renyi graph look like when a rare event happens? This paper answers this question when p is fixed and n tends to infinity by establishing a large deviation principle under an appropriate topology. The formulation and…

Probability · Mathematics 2011-04-05 Sourav Chatterjee , S. R. S. Varadhan

In 2007 we introduced a general model of sparse random graphs with independence between the edges. The aim of this paper is to present an extension of this model in which the edges are far from independent, and to prove several results…

Probability · Mathematics 2011-05-05 Bela Bollobas , Svante Janson , Oliver Riordan

Partial duality generalizes the fundamental concept of the geometric dual of an embedded graph. A partial dual is obtained by forming the geometric dual with respect to only a subset of edges. While geometric duality preserves the genus of…

Combinatorics · Mathematics 2013-11-18 Iain Moffatt

The theory of graphons is an important tool in understanding properties of large networks. We investigate a power-law random graph model and cast it in the graphon framework. The distinctively different structures of the limit graph are…

Probability · Mathematics 2022-08-22 Mei Yin

Two-sample hypothesis testing for random graphs arises naturally in neuroscience, social networks, and machine learning. In this paper, we consider a semiparametric problem of two-sample hypothesis testing for a class of latent position…

Methodology · Statistics 2015-06-19 Minh Tang , Avanti Athreya , Daniel L. Sussman , Vince Lyzinski , Carey E. Priebe

In this paper, the problem of matching pairs of correlated random graphs with multi-valued edge attributes is considered. Graph matching problems of this nature arise in several settings of practical interest including social network…

Information Theory · Computer Science 2018-02-06 F. Shirani , S. Garg , E. Erkip

A graph $G$ with four or more vertices is called bicritical if the removal of any pair of distinct vertices of $G$ results in a graph with a perfect matching. A bicritical graph is minimal if the deletion of each edge results in a…

Combinatorics · Mathematics 2024-10-15 Jing Guo , Hailun Wu , Heping Zhang

We present and investigate an extension of the classical random graph to a general class of inhomogeneous random graph models, where vertices come in different types, and the probability of realizing an edge depends on the types of its…

Statistical Mechanics · Physics 2009-11-07 Bo Soderberg

Specify a randomized algorithm that, given a very large graph or network, extracts a random subgraph. What can we learn about the input graph from a single subsample? We derive laws of large numbers for the sampler output, by relating…

Statistics Theory · Mathematics 2017-10-13 Peter Orbanz