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Journal of Computer and System Sciences
Article . 2024 . Peer-reviewed
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Article . 2024
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https://dx.doi.org/10.48550/ar...
Article . 2021
License: arXiv Non-Exclusive Distribution
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Article . 2024
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Article . 2021
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On kernels for d-path vertex cover

On kernels for \(d\)-path vertex cover
Authors: Radovan Cervený; Pratibha Choudhary; Ondrej Suchý 0001;

On kernels for d-path vertex cover

Abstract

In this paper we study the kernelization of the $d$-Path Vertex Cover ($d$-PVC) problem. Given a graph $G$, the problem requires finding whether there exists a set of at most $k$ vertices whose removal from $G$ results in a graph that does not contain a path (not necessarily induced) with $d$ vertices. It is known that $d$-PVC is NP-complete for $d\geq 2$. Since the problem generalizes to $d$-Hitting Set, it is known to admit a kernel with $\mathcal{O}(dk^d)$ edges. We improve on this by giving better kernels. Specifically, we give kernels with $\mathcal{O}(k^2)$ vertices and edges for the cases when $d=4$ and $d=5$. Further, we give a kernel with $\mathcal{O}(k^4d^{2d+9})$ vertices and edges for general $d$.

Country
Germany
Keywords

FOS: Computer and information sciences, expansion lemma, \(d\)-hitting set, Computer science, 004, \(d\)-path vertex cover, d-Path Vertex Cover, Parameterized complexity, d-Hitting Set, Expansion Lemma, kernelization, Computer Science - Data Structures and Algorithms, Kernelization, Data Structures and Algorithms (cs.DS), parameterized complexity

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green