Improved Kernelization and Fixed-parameter Algorithms for Bicluster Editing

Fuente: arXiv
Gespeichert in:
Bibliographische Detailangaben
1. Verfasser: Lafond, Manuel
Format: Preprint
Veröffentlicht: 2024
Schlagworte:
Online-Zugang:
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
_version_ 1866910662478790656
author Lafond, Manuel
author_facet Lafond, Manuel
contents Given a bipartite graph $G$, the \textsc{Bicluster Editing} problem asks for the minimum number of edges to insert or delete in $G$ so that every connected component is a bicluster, i.e. a complete bipartite graph. This has several applications, including in bioinformatics and social network analysis. In this work, we study the parameterized complexity under the natural parameter $k$, which is the number of allowed modified edges. We first show that one can obtain a kernel with $4.5k$ vertices, an improvement over the previously known quadratic kernel. We then propose an algorithm that runs in time $O^*(2.581^k)$. Our algorithm has the advantage of being conceptually simple and should be easy to implement.
format Preprint
id arxiv_https___arxiv_org_abs_2410_13123
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Improved Kernelization and Fixed-parameter Algorithms for Bicluster Editing
Lafond, Manuel
Data Structures and Algorithms
Given a bipartite graph $G$, the \textsc{Bicluster Editing} problem asks for the minimum number of edges to insert or delete in $G$ so that every connected component is a bicluster, i.e. a complete bipartite graph. This has several applications, including in bioinformatics and social network analysis. In this work, we study the parameterized complexity under the natural parameter $k$, which is the number of allowed modified edges. We first show that one can obtain a kernel with $4.5k$ vertices, an improvement over the previously known quadratic kernel. We then propose an algorithm that runs in time $O^*(2.581^k)$. Our algorithm has the advantage of being conceptually simple and should be easy to implement.
title Improved Kernelization and Fixed-parameter Algorithms for Bicluster Editing
topic Data Structures and Algorithms
url https://arxiv.org/abs/2410.13123