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A graph homomorphism is a vertex map which carries edges from a source graph to edges in a target graph. The instances of the Weighted Maximum H-Colourable Subgraph problem (MAX H-COL) are edge-weighted graphs G and the objective is to find…

Discrete Mathematics · Computer Science 2009-11-18 Robert Engström , Tommy Färnqvist , Peter Jonsson , Johan Thapper

We study the connections between the notions of combinatorial discrepancy and graph degeneracy. In particular, we prove that the maximum discrepancy over all subgraphs $H$ of a graph $G$ of the neighborhood set system of $H$ is sandwiched…

Discrete Mathematics · Computer Science 2021-11-30 Mario Grobler , Yiting Jiang , Patrice Ossona de Mendez , Sebastian Siebertz , Alexandre Vigny

Local complement is a graph operation formalized by Bouchet which replaces the neighborhood of a chosen vertex with its edge-complement. This operation induces an equivalence relation on graphs; determining the size of the resulting…

Combinatorics · Mathematics 2026-03-02 Nicholas Connolly , Shin Nishio , Kae Nemoto

Given a stream of items each associated with a numerical value, its edit distance to monotonicity is the minimum number of items to remove so that the remaining items are non-decreasing with respect to the numerical value. The space…

Data Structures and Algorithms · Computer Science 2011-11-24 Ho-Leung Chan , Tak-Wah Lam , Lap-Kei Lee , Jiangwei Pan , Hing-Fung Ting , Qin Zhang

Let $G$ be a connected graph with vertex set $V$. The distance, $d_G(u, v)$, between vertices $u$ and $v$ of $G$ is defined as the length of a shortest path between $u$ and $v$ in $G$. The distance matrix of $G$ is the matrix $\mathbf{D}(G)…

Combinatorics · Mathematics 2026-02-13 Miriam Abdón , Lilian Markenzon , Cybele T. M. Vinagre

Metric graphs are ubiquitous in science and engineering. For example, many data are drawn from hidden spaces that are graph-like, such as the cosmic web. A metric graph offers one of the simplest yet still meaningful ways to represent the…

Computational Geometry · Computer Science 2017-12-05 Tamal K. Dey , Dayu Shi , Yusu Wang

For a connected graph $G$ of order at least $2$ and $S\subseteq V(G)$, the \emph{Steiner distance} $d_G(S)$ among the vertices of $S$ is the minimum size among all connected subgraphs whose vertex sets contain $S$. In this paper, we…

Combinatorics · Mathematics 2017-08-22 Yaping Mao

The metric dimension dim(G) of a graph $G$ is the minimum cardinality of a subset $S$ of vertices of $G$ such that each vertex of $G$ is uniquely determined by its distances to $S$. It is well-known that the metric dimension of a graph can…

Combinatorics · Mathematics 2022-06-03 Nicolas Bousquet , Quentin Deschamps , Aline Parreau , Ignacio M. Pelayo

In this paper we define a novel edit distance for merge trees, which we argue to be suitable for a good range of applications. Relying also on some technical results contained in other works, we investigate its stability properties, which…

Metric Geometry · Mathematics 2024-11-22 Matteo Pegoraro

We study the evolution of the graph distance and weighted distance between two fixed vertices in dynamically growing random graph models. More precisely, we consider preferential attachment models with power-law exponent $\tau\in(2,3)$,…

Probability · Mathematics 2023-08-15 Joost Jorritsma , Júlia Komjáthy

If $G$ is a graph then a subgraph $H$ is $isometric$ if, for every pair of vertices $u,v$ of $H$, we have $d_H(u,v) = d_G(u,v)$ where $d$ is the distance function. We say a graph $G$ is $distance\ preserving\ (dp)$ if it has an isometric…

Combinatorics · Mathematics 2015-11-16 M. H. Khalifeh , Bruce E. Sagan , Emad Zahedi

Large-scale graphs are widely used to represent object relationships in many real world applications. The occurrence of large-scale graphs presents significant computational challenges to process, analyze, and extract information. Graph…

Social and Information Networks · Computer Science 2019-10-11 Yu Jin , Andreas Loukas , Joseph F. JaJa

Several measures exist for string similarity, including notable ones like the edit distance and the indel distance. The former measures the count of insertions, deletions, and substitutions required to transform one string into another,…

Data Structures and Algorithms · Computer Science 2024-10-15 Sudatta Bhattacharya , Sanjana Dey , Elazar Goldenberg , Michal Koucký

We define a (pseudo-)distance between graphs based on the spectrum of the normalized Laplacian, which is easy to compute or to estimate numerically. It can therefore serve as a rough classification of large empirical graphs into families…

Spectral Theory · Mathematics 2019-04-03 Jiao Gu , Jürgen Jost , Shiping Liu , Peter F. Stadler

Graph embeddings have emerged as a powerful tool for representing complex network structures in a low-dimensional space, enabling the use of efficient methods that employ the metric structure in the embedding space as a proxy for the…

Social and Information Networks · Computer Science 2024-04-18 Radosław Nowak , Adam Małkowski , Daniel Cieślak , Piotr Sokół , Paweł Wawrzyński

An added edge to a graph is called an inset edge. Predicting k inset edges which minimize the average distance of a graph is known to be NP-Hard. When k = 1 the complexity of the problem is polynomial. In this paper, we further find the…

Data Structures and Algorithms · Computer Science 2020-08-14 M. H. Khalifeh , A. -H. Esfahanian

A graph $G$ is $\textit{universal}$ for a (finite) family $\mathcal{H}$ of graphs if every $H \in \mathcal{H}$ is a subgraph of $G$. For a given family $\mathcal{H}$, the goal is to determine the smallest number of edges an…

Combinatorics · Mathematics 2024-01-12 Noga Alon , Natalie Dodson , Carmen Jackson , Rose McCarty , Rajko Nenadov , Lani Southern

The hereditary discrepancy of a set system is a certain quantitative measure of the pseudorandom properties of the system. Roughly, hereditary discrepancy measures how well one can $2$-color the elements of the system so that each set…

Data Structures and Algorithms · Computer Science 2024-04-23 Greg Bodwin , Chengyuan Deng , Jie Gao , Gary Hoppenworth , Jalaj Upadhyay , Chen Wang

There have lately been several suggestions for parametrized distances on a graph that generalize the shortest path distance and the commute time or resistance distance. The need for developing such distances has risen from the observation…

Machine Learning · Statistics 2015-03-17 Ilkka Kivimäki , Masashi Shimbo , Marco Saerens

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…