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The splitting number of a graph $G=(V,E)$ is the minimum number of vertex splits required to turn $G$ into a planar graph, where a vertex split removes a vertex $v \in V$, introduces two new vertices $v_1, v_2$, and distributes the edges…

Computational Geometry · Computer Science 2022-09-09 Martin Nöllenburg , Manuel Sorge , Soeren Terziadis , Anaïs Villedieu , Hsiang-Yun Wu , Jules Wulms

A \emph{spanner} of a graph $G$ is a subgraph $H$ that approximately preserves shortest path distances in $G$. Spanners are commonly applied to compress computation on metric spaces corresponding to weighted input graphs. Classic spanner…

Discrete Mathematics · Computer Science 2021-06-30 Reyan Ahmed , Greg Bodwin , Faryad Darabi Sahneh , Stephen Kobourov , Richard Spence

For a fixed graph $H$, we say that an edge-colored graph $G$ is \emph{weakly $H$-rainbow saturated} if there exists an ordering $e_1, e_2, \ldots, e_m$ of $E\left(\overline{G}\right)$ such that, for any list $c_1, c_2, \ldots, c_m$ of…

Combinatorics · Mathematics 2025-01-07 Xihe Li , Jie Ma , Tianying Xie

For a graph $G$ and $t,k\in\mathbb{Z}^+$ a \emph{$t$-tone $k$-coloring} of $G$ is a function $f:V(G)\rightarrow \binom{[k]}{t}$ such that $|f(v)\cap f(w)| < d(v,w)$ for all distinct $v,w \in V(G)$. The \emph{$t$-tone chromatic number} of…

Combinatorics · Mathematics 2023-06-27 Daniel W. Cranston , Hudson LaFayette

A \emph{proper $t$-edge-coloring} of a graph $G$ is a mapping $\alpha: E(G)\rightarrow \{1,\ldots,t\}$ such that all colors are used, and $\alpha(e)\neq \alpha(e^{\prime})$ for every pair of adjacent edges $e,e^{\prime}\in E(G)$. If $\alpha…

Combinatorics · Mathematics 2017-01-31 Petros A. Petrosyan , Hrant H. Khachatrian

For a graph $G$ in which vertices are either black or white, a zero forcing process is an iterative vertex color changing process such that the only white neighbor of a black vertex becomes black in the next time step. A zero forcing set is…

Combinatorics · Mathematics 2025-08-26 Hau-Yi Lin , Wu-Hsiung Lin , Gerard Jennhwa Chang

We study vulnerability of a uniformly distributed random graph to an attack by an adversary who aims for a global change of the distribution while being able to make only a local change in the graph. We call a graph property $A$…

Discrete Mathematics · Computer Science 2023-04-11 Sergei Kiselev , Andrey Kupavskii , Oleg Verbitsky , Maksim Zhukovskii

A $t$-spanner of a weighted undirected graph $G=(V,E)$, is a subgraph $H$ such that $d_H(u,v)\le t\cdot d_G(u,v)$ for all $u,v\in V$. The sparseness of the spanner can be measured by its size (the number of edges) and weight (the sum of all…

Data Structures and Algorithms · Computer Science 2014-05-01 Michael Elkin , Ofer Neiman , Shay Solomon

Given a graph $I=(V, E),$ $\emptyset \ne D \subseteq V,$ and an arbitrary nonempty set $X,$ an injective function $f: V\to 2^X \setminus \{\emptyset\}$ is an interference of $D$ with respect to $I,$ if for every vertex $u\in V\setminus D$…

Combinatorics · Mathematics 2021-06-21 B. D. Acharya , Germina K. A. , Rency Kurian , Viji Paul , Thomas Zaslavsky

In this study, a spectral graph-theoretic grouping strategy for weakly supervised classification is introduced, where a limited number of labelled samples and a larger set of unlabelled samples are used to construct a larger annotated…

Machine Learning · Computer Science 2015-08-04 Tameem Adel , Alexander Wong , Daniel Stashuk

Many modern applications involve accessing and processing graphical data, i.e. data that is naturally indexed by graphs. Examples come from internet graphs, social networks, genomics and proteomics, and other sources. The typically large…

Information Theory · Computer Science 2023-01-18 Payam Delgosha , Venkat Anantharam

A path separator of a graph $G$ is a set of paths $\mathcal{P}=\{P_1,\ldots,P_t\}$ such that for every pair of edges $e,f\in E(G)$, there exist paths $P_e,P_f\in\mathcal{P}$ such that $e\in E(P_e)$, $f\not\in E(P_e)$, $e\not\in E(P_f)$ and…

Combinatorics · Mathematics 2016-06-03 József Balogh , Béla Csaba , Ryan R. Martin , András Pluhár

The crossing number of a graph $G$ is the least number of crossings over all possible drawings of $G$. We present a structural characterization of graphs with crossing number one.

Combinatorics · Mathematics 2021-08-24 André C. Silva , Alan Arroyo , R. Bruce Richter , Orlando Lee

Let $G$ be a graph, and let $w: V(G) \to \mathbb{R}$ be a weight function on the vertices of $G$. For every subset $X$ of $V(G)$, let $w(X)=\sum_{v \in X} w(v).$ A non-empty subset $S \subset V(G)$ is a weighted safe set of $(G,w)$ if, for…

Combinatorics · Mathematics 2018-05-31 Shinya Fujita , Tommy Jensen , Boram Park , Tadashi Sakuma

The Floyd-Warshall algorithm is the most popular algorithm for determining the shortest paths between all pairs in a graph. It is very a simple and an elegant algorithm. However, if the graph does not contain any negative weighted edge,…

Data Structures and Algorithms · Computer Science 2021-09-07 Ismail H. Toroslu

Let $G=(V,E)$ be a simple graph. A dominating set of $G$ is a subset $S\subseteq V$ such that every vertex not in $S$ is adjacent to at least one vertex in $S$. The cardinality of a smallest dominating set of $G$, denoted by $\gamma(G)$, is…

Combinatorics · Mathematics 2022-05-06 Nima Ghanbari

We give a deterministic, nearly logarithmic-space algorithm for mild spectral sparsification of undirected graphs. Given a weighted, undirected graph $G$ on $n$ vertices described by a binary string of length $N$, an integer $k\leq \log n$,…

Data Structures and Algorithms · Computer Science 2020-04-21 Dean Doron , Jack Murtagh , Salil Vadhan , David Zuckerman

Let $G_{1}$ and $G_{2}$ be disjoint copies of a graph $G$, and let $g:V(G_{1})\rightarrow V(G_{2})$ be a function. A functigraph $F_{G}$ consists of the vertex set $V(G_{1})\cup V(G_{2})$ and the edge set $E(G_{1})\cup E(G_{2})\cup…

Combinatorics · Mathematics 2016-12-06 Muhammad Fazil , Muhammad Mutaza , Usman Ali , Imran Javaid

We present an algorithm to identify sparse dependence structure in continuous and non-Gaussian probability distributions, given a corresponding set of data. The conditional independence structure of an arbitrary distribution can be…

Machine Learning · Computer Science 2017-11-07 Rebecca E. Morrison , Ricardo Baptista , Youssef Marzouk

Graph signal processing (GSP) provides a powerful framework for analyzing signals arising in a variety of domains. In many applications of GSP, multiple network structures are available, each of which captures different aspects of the same…

Machine Learning · Statistics 2021-11-03 Michael Weylandt , George Michailidis , T. Mitchell Roddenberry