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Generalized Tur\'an problems have been a central topic of study in extremal combinatorics throughout the last few decades. One such problem, maximizing the number of cliques of a fixed order in a graph with fixed number of vertices and…

Combinatorics · Mathematics 2021-06-10 Debsoumya Chakraborti , Da Qi Chen

Compression and sparsification algorithms are frequently applied in a preprocessing step before analyzing or optimizing large networks/graphs. In this paper we propose and study a new framework contracting edges of a graph (merging vertices…

Data Structures and Algorithms · Computer Science 2019-02-14 Aaron Bernstein , Karl Däubel , Yann Disser , Max Klimm , Torsten Mütze , Frieder Smolny

We investigate the estimation of the perimeter of a set by a graph cut of a random geometric graph. For $\Omega \subset D = (0,1)^d$, with $d \geq 2$, we are given $n$ random i.i.d. points on $D$ whose membership in $\Omega$ is known. We…

Statistics Theory · Mathematics 2016-08-16 Nicolás García Trillos , Dejan Slepčev , James von Brecht

We prove that a simple distributed algorithm finds a constant approximation of an optimal distance-$k$ dominating set in graphs with no $K_{2,t}$-minor. The algorithm runs in a constant number of rounds. We further show how this procedure…

Data Structures and Algorithms · Computer Science 2022-03-08 Andrzej Czygrinow , Michał Hanćkowiak , Marcin Witkowski

An algorithm is developed for finding a close to optimal junction tree of a given graph G. The algorithm has a worst case complexity O(c^k n^a) where a and c are constants, n is the number of vertices, and k is the size of the largest…

Data Structures and Algorithms · Computer Science 2013-02-18 Ann Becker , Dan Geiger

In $K$-means classification, a set of data will form clusters, i.e. classes, if the measured distances between data points (or some common point in each class) are below a certain threshold. With the assumption that the data points are…

Probability · Mathematics 2016-02-12 Robert A. Murphy

We prove a Poisson limit theorem in the total variation distance of functionals of a general Poisson point process using the Malliavin-Stein method. Our estimates only involve first and second order difference operators and are closely…

Probability · Mathematics 2019-05-28 Jens Grygierek

Maximal clique enumeration appears in various real-world networks, such as social networks and protein-protein interaction networks for different applications. For general graph inputs, the number of maximal cliques can be up to…

Discrete Mathematics · Computer Science 2023-03-14 Hodaka Yamaji

Consider the geometric graph on $n$ independent uniform random points in a connected compact region $A$ of ${\bf R}^d, d \geq 2$, with $C^2$ boundary, or in the unit square, with distance parameter $r_n$. Let $K_n$ be the number of…

Probability · Mathematics 2026-04-09 Mathew D. Penrose , Xiaochuan Yang

We introduce a new way to sample inhomogeneous random graphs designed to have a lot of flexibility in the assignment of the degree sequence and the individual edge probabilities while remaining tractable. To achieve this we run a Poisson…

Probability · Mathematics 2020-03-03 Lorenzo Federico

Let $G=(V,E)$ be a finite, connected graph. We consider a greedy selection of vertices: given a list of vertices $x_1, \dots, x_k$, take $x_{k+1}$ to be any vertex maximizing the sum of distances to the existing vertices and iterate: we…

Combinatorics · Mathematics 2022-05-06 Stefan Steinerberger

Let S_{n,k} denote the random geometric graph obtained by placing points inside a square of area n according to a Poisson point process of intensity 1 and joining each such point to the k=k(n) points of the process nearest to it. In this…

Probability · Mathematics 2013-09-18 Victor Falgas-Ravry

In directed random graphs, in which edges can be assigned to have one of two directions, or perhaps both, the distance between two vertices $v$ and $v'$ can be computed along paths that are directed from $v$ to $v'$, or along paths that are…

Probability · Mathematics 2026-03-25 A. D. Barbour , Gesine Reinert

In this paper we establish asymptotics (as the size of the graph grows to infinity) for the expected number of cliques in the Chung--Lu inhomogeneous random graph model in which vertices are assigned independent weights which have tail…

Probability · Mathematics 2024-11-08 Fraser Daly , Alastair Haig , Seva Shneer

Finding cohesive subgraphs in a large graph has many important applications, such as community detection and biological network analysis. Clique is often a too strict cohesive structure since communities or biological modules rarely form as…

Data Structures and Algorithms · Computer Science 2024-06-11 Qihao Cheng , Da Yan , Tianhao Wu , Lyuheng Yuan , Ji Cheng , Zhongyi Huang , Yang Zhou

Let $S$ be an orientable surface with negative Euler characteristic. For $k \in \mathbb{N}$, let $\mathcal{C}_{k}(S)$ denote the $\textit{k-curve graph}$, whose vertices are isotopy classes of essential simple closed curves on $S$, and…

Geometric Topology · Mathematics 2015-11-17 Tarik Aougab

We consider a problem of approximating the size of the largest clique in a graph, with a monotone circuit. Concretely, we focus on distinguishing a random Erd\H{o}s-Renyi graph $\mathcal{G}_{n,p}$, with $p=n^{-\frac{2}{\alpha-1}}$ chosen…

Computational Complexity · Computer Science 2025-01-17 Jarosław Błasiok , Linus Meierhöfer

We investigate the statistical properties of cut sizes generated by heuristic algorithms which solve approximately the graph bisection problem. On an ensemble of sparse random graphs, we find empirically that the distribution of the cut…

Statistical Mechanics · Physics 2007-05-23 G. R. Schreiber , O. C. Martin

In this work, we consider the problem of sampling a $k$-clique in a graph from an almost uniform distribution in sublinear time in the general graph query model. Specifically the algorithm should output each $k$-clique with probability…

Data Structures and Algorithms · Computer Science 2020-12-09 Talya Eden , Dana Ron , Will Rosenbaum

Consider a weighted or unweighted k-nearest neighbor graph that has been built on n data points drawn randomly according to some density p on R^d. We study the convergence of the shortest path distance in such graphs as the sample size…

Machine Learning · Computer Science 2012-07-10 Morteza Alamgir , Ulrike von Luxburg