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We consider uniform random cographs (either labeled or unlabeled) of large size. Our first main result is the convergence towards a Brownian limiting object in the space of graphons. We then show that the degree of a uniform random vertex…

We prove that any quasirandom uniform hypergraph $H$ can be approximately decomposed into any collection of bounded degree hypergraphs with almost as many edges. In fact, our results also apply to multipartite hypergraphs and even to the…

Combinatorics · Mathematics 2021-01-22 Stefan Ehard , Felix Joos

We introduce probability-graphons which are probability kernels that generalize graphons to the case of weighted graphs. Probability-graphons appear as the limit objects to study sequences of large weighted graphs whose distribution of…

Discrete Mathematics · Computer Science 2025-06-12 Romain Abraham , Jean-François Delmas , Julien Weibel

We introduce a natural notion of mean (or average) distance in the context of compact metric graphs, and study its relation to geometric properties of the graph. We show that it exhibits a striking number of parallels to the reciprocal of…

Combinatorics · Mathematics 2024-02-01 Luís N. Baptista , James B. Kennedy , Delio Mugnolo

Generally speaking, `almost distance-regular' graphs share some, but not necessarily all, of the regularity properties that characterize distance-regular graphs. In this paper we propose two new dual concepts of almost distance-regularity,…

Combinatorics · Mathematics 2012-07-17 Cristina Dalfó , Edwin R. van Dam , Miquel Angel Fiol , Ernest Garriga

A graph is circle if its vertices are in correspondence with a family of chords in a circle in such a way that every two distinct vertices are adjacent if and only if the corresponding chords have nonempty intersection. Even though there…

Discrete Mathematics · Computer Science 2023-04-04 Flavia Bonomo-Braberman , Guillermo A. Durán , Nina Pardal , Martín D. Safe

We generalize subgraph densities, arising in dense graph limit theory, to Markov spaces (symmetric measures on the square of a standard Borel space). More generally, we define an analogue of the set of homomorphisms in the form of a measure…

Probability · Mathematics 2023-11-13 Dávid Kunszenti-Kovács , László Lovász , Balázs Szegedy

The mincut graph bisection problem involves partitioning the n vertices of a graph into disjoint subsets, each containing exactly n/2 vertices, while minimizing the number of "cut" edges with an endpoint in each subset. When considered over…

Statistical Mechanics · Physics 2010-04-27 Allon G. Percus , Gabriel Istrate , Bruno Goncalves , Robert Z. Sumi , Stefan Boettcher

The $\gamma$-graph of a graph $G$ is the graph whose vertices are labelled by the minimum dominating sets of $G$, in which two vertices are adjacent when their corresponding minimum dominating sets (each of size $\gamma(G)$) intersect in a…

Combinatorics · Mathematics 2020-04-06 Matt DeVos , Adam Dyck , Jonathan Jedwab , Samuel Simon

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 introduce a generalization of graphlets to heterogeneous networks called typed graphlets. Informally, typed graphlets are small typed induced subgraphs. Typed graphlets generalize graphlets to rich heterogeneous networks…

Social and Information Networks · Computer Science 2020-10-28 Ryan A. Rossi , Nesreen K. Ahmed , Aldo Carranza , David Arbour , Anup Rao , Sungchul Kim , Eunyee Koh

We consider the problem of classifying graphs using graph kernels. We define a new graph kernel, called the generalized shortest path kernel, based on the number and length of shortest paths between nodes. For our example classification…

Data Structures and Algorithms · Computer Science 2015-11-20 Linus Hermansson , Fredrik D. Johansson , Osamu Watanabe

We investigate structural properties of large, sparse random graphs through the lens of "sampling convergence" (Borgs et. al. (2017)). Sampling convergence generalizes left convergence to sparse graphs, and describes the limit in terms of a…

Probability · Mathematics 2019-07-04 Christian Borgs , Jennifer T. Chayes , Souvik Dhara , Subhabrata Sen

Graphlets are defined as k-node connected induced subgraph patterns. For an undirected graph, 3-node graphlets include close triangle and open triangle. When k = 4, there are six types of graphlets, e.g., tailed-triangle and clique are two…

Machine Learning · Computer Science 2018-10-09 Xutong Liu , Yu-Zhen Janice Chen , John C. S. Lui , Konstantin Avrachenkov

A paradigm that was successfully applied in the study of both pure and algorithmic problems in graph theory can be colloquially summarized as stating that "any graph is close to being the disjoint union of expanders". Our goal in this paper…

Combinatorics · Mathematics 2015-02-03 Guy Moshkovitz , Asaf Shapira

Graphons are limit objects of sequences of graphs and are used to analyze the behavior of large graphs. Recently, graphon signal processing has been developed to study signal processing on large graphs. A major limitation of this approach…

Signal Processing · Electrical Eng. & Systems 2024-03-26 Feng Ji , Xingchao Jian , Wee Peng Tay

Random geometric graphs result from taking $n$ uniformly distributed points in the unit cube, $[0,1]^d$, and connecting two points if their Euclidean distance is at most $r$, for some prescribed $r$. We show that monotone properties for…

Probability · Mathematics 2007-05-23 Ashish Goel , Sanatan Rai , Bhaskar Krishnamachari

For every fixed graph $H$ and every fixed $0 < \alpha < 1$, we show that if a graph $G$ has the property that all subsets of size $\alpha n$ contain the ``correct'' number of copies of $H$ one would expect to find in the random graph…

Combinatorics · Mathematics 2008-04-07 Raphael Yuster

This work will appear as a chapter in a forthcoming volume titled "Topics in Probabilistic Graph Theory". A theory of scaling limits for random graphs has been developed in recent years. This theory gives access to the large-scale geometric…

Probability · Mathematics 2024-10-18 Louigi Addario-Berry , Christina Goldschmidt

The eccentricity matrix $\epsilon(G)$, of a connected graph $G$ is obtained by retaining the maximum distance from each row and column of the distance matrix of $G$ and the other entries are assigned with 0. In this paper, we discuss the…

Combinatorics · Mathematics 2024-05-01 Anjitha Ashokan , Chithra A