Improved Algorithms for Bicluster Editing

DOI10.1007/978-3-540-79228-4_39zbMath1139.68420OpenAlexW1505812587MaRDI QIDQ3502668

Yong Zhang, Jiong Guo, Christian Komusiewicz, Falk Hüffner

Publication date: 27 May 2008

Published in: Lecture Notes in Computer Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-540-79228-4_39

Mathematics Subject Classification ID

Graph theory (including graph drawing) in computer science (68R10) Approximation algorithms (68W25) Randomized algorithms (68W20)

Related Items (13)

On solving manufacturing cell formation via bicluster editing ⋮ Faster parameterized algorithm for \textsc{Bicluster Editing} ⋮ New heuristics for the bicluster editing problem ⋮ A survey of parameterized algorithms and the complexity of edge modification ⋮ Faster parameterized algorithms for \textsc{Bicluster Editing} and \textsc{Flip Consensus Tree} ⋮ A survey of the algorithmic aspects of modular decomposition ⋮ Complexity and parameterized algorithms for cograph editing ⋮ Even better fixed-parameter algorithms for bicluster editing ⋮ The biclique partitioning polytope ⋮ Complexity of modification problems for reciprocal best match graphs ⋮ A simple and improved parameterized algorithm for bicluster editing ⋮ Hybrid Metaheuristic for Bicluster Editing Problem ⋮ An effective branching strategy based on structural relationship among multiple forbidden induced subgraphs

Cites Work

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• Correlation clustering
• Graph-modeled data clustering: Exact algorithms for clique generation
• NP-hard problems in hierarchical-tree clustering
• Cluster graph modification problems
• Parametrized complexity theory.
• Applying Modular Decomposition to Parameterized Bicluster Editing
• The Cluster Editing Problem: Implementations and Experiments
• A More Effective Linear Kernelization for Cluster Editing
• Efficient Parameterized Preprocessing for Cluster Editing
• Fixed-Parameter Algorithms for Cluster Vertex Deletion
• Going Weighted: Parameterized Algorithms for Cluster Editing
• Aggregating inconsistent information

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