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ACM Transactions on Algorithms
Article . 2026 . Peer-reviewed
Data sources: Crossref
https://doi.org/10.1137/1.9781...
Part of book or chapter of book . 2024 . Peer-reviewed
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https://dx.doi.org/10.48550/ar...
Article . 2023
License: arXiv Non-Exclusive Distribution
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DBLP
Preprint . 2023
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DBLP
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http://dx.doi.org/10.1137/1.97...
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Sparse Induced Subgraphs in P 6 -free Graphs

Authors: Maria Chudnovsky; Rose McCarty; Marcin Pilipczuk; Michał Pilipczuk; Paweł Rzążewski;

Sparse Induced Subgraphs in P 6 -free Graphs

Abstract

We prove that a number of computational problems that ask for the largest sparse induced subgraph satisfying some property definable in \(\mathsf{CMSO}_{2}\) logic, most notably Feedback Vertex Set , are polynomial-time solvable in the class of \(P_{6}\) -free graphs. This generalizes the work of Grzesik, Klimošová, Pilipczuk, and Pilipczuk on the Maximum Weight Independent Set problem in \(P_{6}\) -free graphs [SODA 2019, TALG 2022], and of Abrishami, Chudnovsky, Pilipczuk, Rzążewski, and Seymour on problems in \(P_{5}\) -free graphs [SODA 2021]. The key step is a new generalization of the framework of potential maximal cliques . We show that instead of listing a large family of potential maximal cliques, it is sufficient to only list their carvers : vertex sets that contain the same vertices from the sought solution and have similar separation properties.

Keywords

FOS: Computer and information sciences, Discrete Mathematics (cs.DM), Computer Science - Data Structures and Algorithms, FOS: Mathematics, Mathematics - Combinatorics, Data Structures and Algorithms (cs.DS), Combinatorics (math.CO), Computer Science - Discrete Mathematics

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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