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Related papers: Harmless Sets in Sparse Classes

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Given a graph $G = (V,E)$, a threshold function $t~ :~ V \rightarrow \mathbb{N}$ and an integer $k$, we study the Harmless Set problem, where the goal is to find a subset of vertices $S \subseteq V$ of size at least $k$ such that every…

Computational Complexity · Computer Science 2022-01-27 Ajinkya Gaikwad , Soumen Maity

Inspired by the potential of improving tractability via gap- or above-guarantee parametrisations, we investigate the complexity of Dominating Set when given a suitable lower-bound witness. Concretely, we consider being provided with a…

Data Structures and Algorithms · Computer Science 2019-06-24 Carl Einarson , Felix Reidl

A secure set $S$ in a graph is defined as a set of vertices such that for any $X\subseteq S$ the majority of vertices in the neighborhood of $X$ belongs to $S$. It is known that deciding whether a set $S$ is secure in a graph is…

Computational Complexity · Computer Science 2017-07-11 Bernhard Bliem , Stefan Woltran

In this paper we study the problem of finding a small safe set $S$ in a graph $G$, i.e. a non-empty set of vertices such that no connected component of $G[S]$ is adjacent to a larger component in $G - S$. We enhance our understanding of the…

Computational Complexity · Computer Science 2019-02-01 Rémy Belmonte , Tesshu Hanaka , Ioannis Katsikarelis , Michael Lampis , Hirotaka Ono , Yota Otachi

We study a generalization of the classic Spanning Tree problem that allows for a non-uniform failure model. More precisely, edges are either \emph{safe} or \emph{unsafe} and we assume that failures only affect unsafe edges. In Unweighted…

Discrete Mathematics · Computer Science 2024-02-29 Matthias Bentert , Jannik Schestag , Frank Sommer

In this paper, we study the Target Set Selection problem from a parameterized complexity perspective. Here for a given graph and a threshold for each vertex, the task is to find a set of vertices (called a target set) which activates the…

Data Structures and Algorithms · Computer Science 2020-08-17 Pavel Dvořák , Dušan Knop , Tomáš Toufar

Sparse structures are frequently sought when pursuing tractability in optimization problems. They are exploited from both theoretical and computational perspectives to handle complex problems that become manageable when sparsity is present.…

Discrete Mathematics · Computer Science 2019-03-21 Yuri Faenza , Gonzalo Muñoz , Sebastian Pokutta

The Target Set Selection problem takes as an input a graph $G$ and a non-negative integer threshold $ \mbox{thr}(v) $ for every vertex $v$. A vertex $v$ can get active as soon as at least $ \mbox{thr}(v) $ of its neighbors have been…

Discrete Mathematics · Computer Science 2017-10-03 Tim A. Hartmann

Hitting Set is a classic problem in combinatorial optimization. Its input consists of a set system F over a finite universe U and an integer t; the question is whether there is a set of t elements that intersects every set in F. The Hitting…

Data Structures and Algorithms · Computer Science 2015-07-27 Bart M. P. Jansen

We prove that for every positive integer $r$ and for every graph class $\mathcal G$ of bounded expansion, the $r$-Dominating Set problem admits a linear kernel on graphs from $\mathcal G$. Moreover, when $\mathcal G$ is only assumed to be…

We show that the dominating set problem parameterized by solution size is fixed-parameter tractable (FPT) in graphs that do not contain the claw (K(1,3)), the complete bipartite graph on four vertices where the two parts have one and three…

Data Structures and Algorithms · Computer Science 2015-03-17 Marek Cygan , Geevarghese Philip , Marcin Pilipczuk , Michał Pilipczuk , Jakub Onufry Wojtaszczyk

The theoretical notions of graph classes with bounded expansion and that are nowhere dense are meant to capture structural sparsity of real world networks that can be used to design efficient algorithms. In the area of sparse graphs, the…

Data Structures and Algorithms · Computer Science 2018-11-20 Wojciech Nadara

The performance of trained neural networks is robust to harsh levels of pruning. Coupled with the ever-growing size of deep learning models, this observation has motivated extensive research on learning sparse models. In this work, we focus…

Machine Learning · Computer Science 2022-11-29 Jose Gallego-Posada , Juan Ramirez , Akram Erraqabi , Yoshua Bengio , Simon Lacoste-Julien

We study the parameterized complexity of the directed variant of the classical {\sc Steiner Tree} problem on various classes of directed sparse graphs. While the parameterized complexity of {\sc Steiner Tree} parameterized by the number of…

Data Structures and Algorithms · Computer Science 2012-10-02 Mark Jones , Daniel Lokshtanov , M. S. Ramanujan , Saket Saurabh , Ondřej Suchý

Given a graph $G=(V,E)$, a set $\mathcal{F}$ of forbidden subgraphs, we study $\mathcal{F}$-Free Edge Deletion, where the goal is to remove minimum number of edges such that the resulting graph does not contain any $F\in \mathcal{F}$ as a…

Data Structures and Algorithms · Computer Science 2021-02-12 Ajinkya Gaikwad , Soumen Maity

In this paper, we consider the Target Set Selection problem: given a graph and a threshold value $thr(v)$ for any vertex $v$ of the graph, find a minimum size vertex-subset to "activate" s.t. all the vertices of the graph are activated at…

Computational Complexity · Computer Science 2015-06-11 Cristina Bazgan , Morgan Chopin , André Nichterlein , Florian Sikora

In this paper, we are interested in learning the underlying graph structure behind training data. Solving this basic problem is essential to carry out any graph signal processing or machine learning task. To realize this, we assume that the…

Machine Learning · Computer Science 2018-05-08 Sundeep Prabhakar Chepuri , Sijia Liu , Geert Leus , Alfred O. Hero

The recently introduced graph parameter tree-cut width plays a similar role with respect to immersions as the graph parameter treewidth plays with respect to minors. In this paper, we provide the first algorithmic applications of tree-cut…

Data Structures and Algorithms · Computer Science 2022-06-03 Robert Ganian , Eun Jung Kim , Stefan Szeider

For a graph $H$, a graph $G$ is an $H$-graph if it is an intersection graph of connected subgraphs of some subdivision of $H$. $H$-graphs naturally generalize several important graph classes like interval or circular-arc graph. This class…

Data Structures and Algorithms · Computer Science 2020-02-24 Fedor V. Fomin , Petr A. Golovach , Jean-Florent Raymond

A theorem of Ding, Oporowski, Oxley, and Vertigan implies that any sufficiently large twin-free graph contains a large matching, a co-matching, or a half-graph as a semi-induced subgraph. The sizes of these unavoidable patterns are measured…

Computational Complexity · Computer Science 2026-02-10 Jan Dreier , Nikolas Mählmann , Sebastian Siebertz
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