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For $n\geq 3$, let $r=r(n)\geq 3$ be an integer. A hypergraph is $r$-uniform if each edge is a set of $r$ vertices, and is said to be linear if two edges intersect in at most one vertex. In this paper, the number of linear $r$-uniform…

Combinatorics · Mathematics 2019-08-20 Brendan D. McKay , Fang Tian

Given a labeled graph, the frequent-subgraph mining (FSM) problem asks to find all the $k$-vertex subgraphs that appear with frequency greater than a given threshold. FSM has numerous applications ranging from biology to network science, as…

Data Structures and Algorithms · Computer Science 2018-09-11 Cigdem Aslay , Muhammad Anis Uddin Nasir , Gianmarco De Francisci Morales , Aristides Gionis

A hypergraph is Sperner if no hyperedge contains another one. A Sperner hypergraph is equilizable (resp., threshold) if the characteristic vectors of its hyperedges are the (minimal) binary solutions to a linear equation (resp., inequality)…

Combinatorics · Mathematics 2018-05-29 Endre Boros , Vladimir Gurvich , Martin Milanič

Constructing a spanning tree of a graph is one of the most basic tasks in graph theory. We consider a relaxed version of this problem in the setting of local algorithms. The relaxation is that the constructed subgraph is a sparse spanning…

Data Structures and Algorithms · Computer Science 2021-04-28 Reut Levi , Dana Ron , Ronitt Rubinfeld

Learning a hidden hypergraph is a natural generalization of the classical group testing problem that consists in detecting unknown hypergraph $H_{un}=H(V,E)$ by carrying out edge-detecting tests. In the given paper we focus our attention…

Information Theory · Computer Science 2016-07-05 A. G. D'yachkov , I. V. Vorobyev , N. A. Polyanskii , V. Yu. Shchukin

We analyze the computational complexity of the following computational problems called Bounded-Density Edge Deletion and Bounded-Density Vertex Deletion: Given a graph $G$, a budget $k$ and a target density $\tau_\rho$, are there $k$ edges…

Data Structures and Algorithms · Computer Science 2024-04-15 Cristina Bazgan , André Nichterlein , Sofia Vazquez Alferez

Many machine learning algorithms used for dimensional reduction and manifold learning leverage on the computation of the nearest neighbours to each point of a dataset to perform their tasks. These proximity relations define a so-called…

Statistical Mechanics · Physics 2020-07-22 Vittorio Erba , Sebastiano Ariosto , Marco Gherardi , Pietro Rotondo

In this paper, we consider an analog of the well-studied extremal problem for triangle-free subgraphs of graphs for uniform hypergraphs. A loose triangle is a hypergraph $T$ consisting of three edges $e,f$ and $g$ such that $|e \cap f| = |f…

Combinatorics · Mathematics 2020-05-11 Jiaxi Nie , Sam Spiro , Jacques Verstraete

In a series of recent works, we have generalised the consistency results in the stochastic block model literature to the case of uniform and non-uniform hypergraphs. The present paper continues the same line of study, where we focus on…

Machine Learning · Computer Science 2017-05-18 Debarghya Ghoshdastidar , Ambedkar Dukkipati

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

We consider the problem of constructing a graph of minimum degree $k\ge 1$ in the following controlled random graph process, introduced recently by Frieze, Krivelevich and Michaeli. Suppose the edges of the complete graph on $n$ vertices…

Combinatorics · Mathematics 2024-01-30 Kyriakos Katsamaktsis , Shoham Letzter

An identifying code of a graph is a dominating set which uniquely determines all the vertices by their neighborhood within the code. Whereas graphs with large minimum degree have small domination number, this is not the case for the…

Combinatorics · Mathematics 2017-01-02 Florent Foucaud , Guillem Perarnau , Oriol Serra

We propose neighborhood-based core decomposition: a novel way of decomposing hypergraphs into hierarchical neighborhood-cohesive subhypergraphs. Alternative approaches to decomposing hypergraphs, e.g., reduction to clique or bipartite…

Social and Information Networks · Computer Science 2023-04-11 Naheed Anjum Arafat , Arijit Khan , Arpit Kumar Rai , Bishwamittra Ghosh

Learning a hidden hypergraph is a natural generalization of the classical group testing problem that consists in detecting unknown hypergraph $H_{un}=H(V,E)$ by carrying out edge-detecting tests. In the given paper we focus our attention…

Information Theory · Computer Science 2016-11-18 A. G. D'yachkov , I. V. Vorobyev , N. A. Polyanskii , V. Yu. Shchukin

The semi-random hypergraph process is a natural generalisation of the semi-random graph process, which can be thought of as a one player game. For fixed $r < s$, starting with an empty hypergraph on $n$ vertices, in each round a set of $r$…

Combinatorics · Mathematics 2025-11-20 Natalie Behague , Pawel Pralat , Andrzej Rucinski

We pursue the study of edge-irregulators of graphs, which were recently introduced in [Fioravantes et al. Parametrised Distance to Local Irregularity. IPEC, 2024]. That is, we are interested in the parameter Ie(G), which, for a given graph…

Combinatorics · Mathematics 2025-11-19 Julien Bensmail , Noémie Catherinot , Foivos Fioravantes , Clara Marcille , Nacim Oijid

We consider the structure of $H$-free subgraphs of graphs with high minimal degree. We prove that for every $k>m$ there exists an $\epsilon:=\epsilon(k,m)>0$ so that the following holds. For every graph $H$ with chromatic number $k$ from…

Combinatorics · Mathematics 2017-06-20 Noga Alon , Clara Shikhelman

A $k$-graph (or $k$-uniform hypergraph) $H$ is uniformly dense if the edge distribution of $H$ is uniformly dense with respect to every large collection of $k$-vertex cliques induced by sets of $(k-2)$-tuples. Reiher, R\"odl and Schacht…

Combinatorics · Mathematics 2023-05-03 Hao Lin , Guanghui Wang , Wenling Zhou

We study the algorithmic tractability of finding large independent sets in dense random hypergraphs. In the sparse regime, much of the natural algorithms can be formulated within either the local or the low-degree polynomial (LDP)…

Data Structures and Algorithms · Computer Science 2026-05-08 Abhishek Dhawan , Nhi U. Dinh , Eren C. Kızıldağ , Neeladri Maitra , Bayram A. Şahin

A prominent tool in many problems involving metric spaces is a notion of randomized low-diameter decomposition. Loosely speaking, $\beta$-decomposition refers to a probability distribution over partitions of the metric into sets of low…

Data Structures and Algorithms · Computer Science 2016-09-29 Lior Kamma , Robert Krauthgamer
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