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Related papers: Subhypergraphs in non-uniform random hypergraphs

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We revisit the problem of counting the number of copies of a fixed graph in a random graph or multigraph, for various models of random (multi)graphs. For our proofs we introduce the notion of \emph{patchworks} to describe the possible…

Despite the fact that many important problems (including clustering) can be described using hypergraphs, theoretical foundations as well as practical algorithms using hypergraphs are not well developed yet. In this paper, we propose a…

Combinatorics · Mathematics 2020-07-01 Bogumil Kaminski , Valerie Poulin , Pawel Pralat , Przemyslaw Szufel , Francois Theberge

Subgraph densities have been defined, and served as basic tools, both in the case of graphons (limits of dense graph sequences) and graphings (limits of bounded-degree graph sequences). While limit objects have been described for the…

Combinatorics · Mathematics 2021-05-11 Dávid Kunszenti-Kovács , László Lovász , Balázs Szegedy

Dense subgraph discovery is a fundamental primitive in graph and hypergraph analysis which among other applications has been used for real-time story detection on social media and improving access to data stores of social networking…

Data Structures and Algorithms · Computer Science 2024-02-23 Yufan Huang , David F. Gleich , Nate Veldt

The planted densest subgraph detection problem refers to the task of testing whether in a given (random) graph there is a subgraph that is unusually dense. Specifically, we observe an undirected and unweighted graph on $n$ vertices. Under…

Data Structures and Algorithms · Computer Science 2024-05-06 Wasim Huleihel , Arya Mazumdar , Soumyabrata Pal

We consider large uniform labeled random graphs in different classes with prescribed decorations in their modular decomposition. Our main result is the estimation of the number of copies of every graph as an induced subgraph. As a…

Combinatorics · Mathematics 2023-10-25 Théo Lenoir

In a nutshell, submodular functions encode an intuitive notion of diminishing returns. As a result, submodularity appears in many important machine learning tasks such as feature selection and data summarization. Although there has been a…

Data Structures and Algorithms · Computer Science 2018-03-19 Marko Mitrovic , Moran Feldman , Andreas Krause , Amin Karbasi

Hypergraph is a data structure that enables us to model higher-order associations among data entities. Conventional graph-structured data can represent pairwise relationships only, whereas hypergraph enables us to associate any number of…

Machine Learning · Computer Science 2024-12-10 Md. Tanvir Alam , Chowdhury Farhan Ahmed , Carson K. Leung

Given a hypergraph $\mathcal{H}$, the dual hypergraph of $\mathcal{H}$ is the hypergraph of all minimal transversals of $\mathcal{H}$. The dual hypergraph is always Sperner, that is, no hyperedge contains another. A special case of Sperner…

Combinatorics · Mathematics 2024-05-13 Endre Boros , Vladimir Gurvich , Martin Milanič , Yushi Uno

In the binomial random graph $\mathcal{G}(n,p)$, when $p$ changes from $(1-\varepsilon)/n$ (subcritical case) to $1/n$ and then to $(1+\varepsilon)/n$ (supercritical case) for $\varepsilon>0$, with high probability the order of the largest…

Combinatorics · Mathematics 2018-10-19 Oliver Cooley , Wenjie Fang , Nicola Del Giudice , Mihyun Kang

Random graphs have proven to be one of the most important and fruitful concepts in modern Combinatorics and Theoretical Computer Science. Besides being a fascinating study subject for their own sake, they serve as essential instruments in…

Combinatorics · Mathematics 2007-05-23 Michael Krivelevich , Benny Sudakov

We consider the problem of embedding the nodes of a hypergraph into Euclidean space under the assumption that the interactions arose through closeness to unknown hyperedge centres. In this way, we tackle the inverse problem associated with…

Social and Information Networks · Computer Science 2025-09-11 Francesco Zigliotto , Desmond J. Higham

We introduce a clustering coefficient for nondirected and directed hypergraphs, which we call the quad clustering coefficient. We determine the average quad clustering coefficient and its distribution in real-world hypergraphs and compare…

Physics and Society · Physics 2024-04-08 Gyeong-Gyun Ha , Izaak Neri , Alessia Annibale

Binary classification is one of the most common problem in machine learning. It consists in predicting whether a given element belongs to a particular class. In this paper, a new algorithm for binary classification is proposed using a…

Machine Learning · Computer Science 2019-03-12 Alexandre Quemy

We revisit the problem of counting the number of copies of a fixed graph in a random graph or multigraph, including the case of constrained degrees. Our approach relies heavily on analytic combinatorics and on the notion of patchwork to…

Non-uniform hypergraphs appear in various domains of computer science as in the satisfiability problems and in data analysis. We analyse a general model where the probability for an edge of size $t$ to belong to the hypergraph depends of a…

Combinatorics · Mathematics 2015-03-06 Elie de Panafieu

In recent years many algorithms have been developed for finding patterns in graphs and networks. A disadvantage of these algorithms is that they use subgraph isomorphism to determine the support of a graph pattern; subgraph isomorphism is a…

Data Structures and Algorithms · Computer Science 2015-03-19 Anton Dries , Siegfried Nijssen

We describe a general approach of determining the distribution of spanning subgraphs in the random graph $\G(n,p)$. In particular, we determine the distribution of spanning subgraphs of certain given degree sequences, which is a…

Combinatorics · Mathematics 2015-01-16 Pu Gao

Fractional (hyper-)graph theory is concerned with the specific problems that arise when fractional analogues of otherwise integer-valued (hyper-)graph invariants are considered. The focus of this paper is on fractional edge covers of…

Discrete Mathematics · Computer Science 2023-09-25 Georg Gottlob , Matthias Lanzinger , Reinhard Pichler , Igor Razgon

A new approach of graph matching is introduced in this paper, which efficiently solves the problem of graph isomorphism and subgraph isomorphism. In this paper we are introducing a new approach called SubGraD, for query graph detection in…

Data Structures and Algorithms · Computer Science 2012-05-23 Akshara Pande , Vivekanand Pant , S. Nigam