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We give a survey of basic results on the cut norm and cut metric for graphons (and sometimes more general kernels), with emphasis on the equivalence problem. The main results are not new, but we add various technical complements, and a new…

Combinatorics · Mathematics 2011-06-06 Svante Janson

Graphons have traditionally served as limit objects for dense graph sequences, with the cut distance serving as the metric for convergence. However, sparse graph sequences converge to the trivial graphon under the conventional definition of…

Signal Processing · Electrical Eng. & Systems 2023-09-12 Xingchao Jian , Feng Ji , Wee Peng Tay

Borgs, Chayes, Cohn and Holden (2016+) recently extended the definition of graphons from probability spaces to arbitrary $\sigma$-finite measure spaces, in order to study limits of sparse graphs. They also extended the definition of the cut…

Combinatorics · Mathematics 2016-08-17 Svante Janson

In a recent paper, Caron and Fox suggest a probabilistic model for sparse graphs which are exchangeable when associating each vertex with a time parameter in $\mathbb{R}_+$. Here we show that by generalizing the classical definition of…

Probability · Mathematics 2018-06-21 Christian Borgs , Jennifer T. Chayes , Henry Cohn , Nina Holden

We study a metric on the set of finite graphs in which two graphs are considered to be similar if they have similar bounded dimensional "factors". We show that limits of convergent graph sequences in this metric can be represented by…

Combinatorics · Mathematics 2016-12-07 Dávid Kunszenti-Kovács , László Lovász , Balázs Szegedy

We study four different notions of convergence for graphexes, recently introduced by Borgs, Chayes, Cohn and Holden, and by Veitch and Roy. We give some properties of them and some relations between them. We also extend results by Veitch…

Probability · Mathematics 2022-03-25 Svante Janson

Recently, Bollob\'as, Janson and Riordan introduced a very general family of random graph models, producing inhomogeneous random graphs with $\Theta(n)$ edges. Roughly speaking, there is one model for each {\em kernel}, i.e., each symmetric…

Combinatorics · Mathematics 2010-06-29 B. Bollobas , O. Riordan

In an earlier paper the authors proved that limits of convergent graph sequences can be described by various structures, including certain 2-variable real functions called graphons, random graph models satisfying certain consistency…

Combinatorics · Mathematics 2009-02-10 László Lovász , Balázs Szegedy

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 prove measurable analogues of Whitney's classical theorems on weak isomorphisms of finite graphs. In the setting of locally finite graphings, we introduce a notion of weak isomorphism as an edge-measure-preserving Borel bijection that…

Combinatorics · Mathematics 2026-05-18 Márton Borbényi , Grigory Terlov , László Márton Tóth

Recently, Bollob\'as, Janson and Riordan introduced a family of random graph models producing inhomogeneous graphs with $n$ vertices and $\Theta(n)$ edges whose distribution is characterized by a kernel, i.e., a symmetric measurable…

Probability · Mathematics 2010-02-10 Bela Bollobas , Oliver Riordan

In this paper we introduce a general framework for the study of limits of relational structures in general and graphs in particular, which is based on a combination of model theory and (functional) analysis. We show how the various…

Combinatorics · Mathematics 2021-04-23 Jaroslav Nesetril , Patrice Ossona De Mendez

A graph $G$ is weakly $\gamma$-closed if every induced subgraph of $G$ contains one vertex $v$ such that for each non-neighbor $u$ of $v$ it holds that $|N(u)\cap N(v)|<\gamma$. The weak closure $\gamma(G)$ of a graph, recently introduced…

Discrete Mathematics · Computer Science 2022-11-04 Tomohiro Koana , Christian Komusiewicz , Frank Sommer

We propose graph kernels based on subgraph matchings, i.e. structure-preserving bijections between subgraphs. While recently proposed kernels based on common subgraphs (Wale et al., 2008; Shervashidze et al., 2009) in general can not be…

Machine Learning · Computer Science 2012-07-03 Nils Kriege , Petra Mutzel

The theory of graphons comes with the so-called cut norm and the derived cut distance. The cut norm is finer than the weak* topology (when considering the predual of $L^{1}$-functions). Dole\v{z}al and Hladk\'y [J. Combin. Theory Ser. B 137…

Combinatorics · Mathematics 2022-04-19 Martin Doležal , Jan Grebík , Jan Hladký , Israel Rocha , Václav Rozhoň

We generalize the notion of quasirandom which concerns a class of equivalent properties that random graphs satisfy. We show that the convergence of a graph sequence under the spectral distance is equivalent to the convergence using the…

Combinatorics · Mathematics 2013-11-06 Fan Chung

We prove algorithmic weak and \Szemeredi{} regularity lemmas for several classes of sparse graphs in the literature, for which only weak regularity lemmas were previously known. These include core-dense graphs, low threshold rank graphs,…

Data Structures and Algorithms · Computer Science 2025-05-30 Greg Bodwin , Santosh Vempala

Recent work has introduced sparse exchangeable graphs and the associated graphex framework, as a generalization of dense exchangeable graphs and the associated graphon framework. The development of this subject involves the interplay…

Probability · Mathematics 2020-02-12 Christian Borgs , Jennifer T. Chayes , Henry Cohn , Victor Veitch

We consider the problem of estimating graph limits, known as graphons, from observations of sequences of sparse finite graphs. In this paper we show a simple method that can shed light on a subset of sparse graphs. The method involves…

Machine Learning · Statistics 2025-07-08 Sevvandi Kandanaarachchi , Cheng Soon Ong

Consider a random graph process where vertices are chosen from the interval $[0,1]$, and edges are chosen independently at random, but so that, for a given vertex $x$, the probability that there is an edge to a vertex $y$ decreases as the…

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