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Related papers: Random Schreier graphs as expanders

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A regular graph $G = (V,E)$ is an $(\varepsilon,\gamma)$ small-set expander if for any set of vertices of fractional size at most $\varepsilon$, at least $\gamma$ of the edges that are adjacent to it go outside. In this paper, we give a…

Computational Complexity · Computer Science 2022-11-18 Mark Braverman , Dor Minzer

The graph isomorphism problem looks deceptively simple, but although polynomial-time algorithms exist for certain types of graphs such as planar graphs and graphs with bounded degree or eigenvalue multiplicity, its complexity class is still…

Discrete Mathematics · Computer Science 2025-07-11 Stefan Klus , Patrick Gelß

In the realm of generative models for graphs, extensive research has been conducted. However, most existing methods struggle with large graphs due to the complexity of representing the entire joint distribution across all node pairs and…

Social and Information Networks · Computer Science 2024-05-15 Andreas Bergmeister , Karolis Martinkus , Nathanaël Perraudin , Roger Wattenhofer

In this paper, we study a bipartite analogue of the `random graphs evolving by degrees' process. We are given a bipartitioned set of vertices $V$ into two disjoint parts ${L}$ and ${R}$ and possibly unequal positive constants $\alpha$ and…

Probability · Mathematics 2025-09-30 Neeladri Maitra

Graph symmetries intervene in diverse applications, from enumeration, to graph structure compression, to the discovery of graph dynamics (e.g., node arrival order inference). Whereas Erd\H{o}s-R\'enyi graphs are typically asymmetric, real…

Probability · Mathematics 2018-12-27 Tomasz Luczak , Abram Magner , Wojciech Szpankowski

In statistical mechanical investigations on complex networks, it is useful to employ random graphs ensembles as null models, to compare with experimental realizations. Motivated by transcription networks, we present here a simple way to…

Statistical Mechanics · Physics 2009-11-11 F. Bassetti , M. Cosentino Lagomarsino , B. Bassetti , P. Jona

In a $(1:b)$ biased Maker-Breaker game, how good a strategy is for a player can be measured by the bias range for which its rival can win, choosing an appropriate counterstrategy. Bednarska and {\L}uczak proved that, in the $H$-subgraph…

Combinatorics · Mathematics 2019-07-11 Ander Lamaison

We consider the spectral gap of a uniformly chosen random $(d_1,d_2)$-biregular bipartite graph $G$ with $|V_1|=n, |V_2|=m$, where $d_1,d_2$ could possibly grow with $n$ and $m$. Let $A$ be the adjacency matrix of $G$. Under the assumption…

Probability · Mathematics 2023-06-01 Yizhe Zhu

In this paper, we obtain a precise estimate of the probability that the sparse binomial random graph contains a large number of vertices in a triangle. The estimate of log of this probability is correct up to second order, and enables us to…

Probability · Mathematics 2025-08-21 Suman Chakraborty , Remco van der Hofstad , Frank den Hollander

We prove that random triangulations of high genus contain very large expander subgraphs, answering a question of Benjamini. Our approach relies on new general criteria for arbitrary graphs to contain large expander subgraphs.

Combinatorics · Mathematics 2026-02-18 Tanguy Lions , Baptiste Louf

We investigate the structure of graphs of twin-width at most $1$, and obtain the following results: - Graphs of twin-width at most $1$ are permutation graphs. In particular they have an intersection model and a linear structure. - There is…

Discrete Mathematics · Computer Science 2025-01-03 Jungho Ahn , Hugo Jacob , Noleen Köhler , Christophe Paul , Amadeus Reinald , Sebastian Wiederrecht

Lipschitz extensions were recently proposed as a tool for designing node differentially private algorithms. However, efficiently computable Lipschitz extensions were known only for 1-dimensional functions (that is, functions that output a…

Cryptography and Security · Computer Science 2015-04-30 Sofya Raskhodnikova , Adam Smith

Edge expansion is a parameter indicating how well-connected a graph is. It is useful for designing robust networks, analysing random walks or information flow through a network and is an important notion in theoretical computer science.…

Probability · Mathematics 2026-01-12 Colin McDiarmid , Katarzyna Rybarczyk , Fiona Skerman , Małgorzata Sulkowska

We attempt to better understand randomization in local distributed graph algorithms by exploring how randomness is used and what we can gain from it: - We first ask the question of how much randomness is needed to obtain efficient…

Data Structures and Algorithms · Computer Science 2019-06-04 Mohsen Ghaffari , Fabian Kuhn

The random graph model has recently been extended to a random preferential attachment graph model, in order to enable the study of general asymptotic properties in network types that are better represented by the preferential attachment…

Social and Information Networks · Computer Science 2015-02-10 Chen Avin , Zvi Lotker , David Peleg

We consider the problem of sampling from a distribution on graphs, specifically when the distribution is defined by an evolving graph model, and consider the time, space and randomness complexities of such samplers. In the standard…

Data Structures and Algorithms · Computer Science 2025-09-03 Guy Even , Reut Levi , Moti Medina , Adi Rosen

Random intersection graphs model networks with communities, assuming an underlying bipartite structure of groups and individuals, where these groups may overlap. Group memberships are generated through the bipartite configuration model.…

Probability · Mathematics 2026-01-14 Remco van der Hofstad , Julia Komjathy , Viktoria Vadon

An emerging trend in approximate counting is to show that certain `low-temperature' problems are easy on typical instances, despite worst-case hardness results. For the class of regular graphs one usually shows that expansion can be…

Data Structures and Algorithms · Computer Science 2024-02-06 Charles Carlson , Ewan Davies , Alexandra Kolla

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

We introduce a new approach to constructing networks with realistic features. Our method, in spite of its conceptual simplicity (it has only two parameters) is capable of generating a wide variety of network types with prescribed…

Data Analysis, Statistics and Probability · Physics 2010-04-30 G. Palla , L. Lovasz , T. Vicsek