Fast Biclustering by Dual Parameterization

Authors Pål Grønås Drange, Felix Reidl, Fernando Sánchez Villaamil, Somnath Sikdar



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Pål Grønås Drange
Felix Reidl
Fernando Sánchez Villaamil
Somnath Sikdar

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Pål Grønås Drange, Felix Reidl, Fernando Sánchez Villaamil, and Somnath Sikdar. Fast Biclustering by Dual Parameterization. In 10th International Symposium on Parameterized and Exact Computation (IPEC 2015). Leibniz International Proceedings in Informatics (LIPIcs), Volume 43, pp. 402-413, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2015) https://doi.org/10.4230/LIPIcs.IPEC.2015.402

Abstract

We study two clustering problems, Starforest Editing, the problem of adding and deleting edges to obtain a disjoint union of stars, and the generalization Bicluster Editing. We show that, in addition to being NP-hard, none of the problems can be solved in subexponential time unless the exponential time hypothesis fails.
 
Misra, Panolan, and Saurabh (MFCS 2013) argue that introducing a bound on the  number of connected components in the solution should not make the problem  easier: In particular, they argue that the subexponential time algorithm for editing to a fixed number of clusters (p-Cluster Editing) by Fomin et al. (J. Comput. Syst. Sci., 80(7) 2014) is an exception rather than the rule. Here, p is a secondary parameter, bounding the number of components in the solution.

However, upon bounding the number of stars or bicliques in the solution, we obtain algorithms which run in time O(2^{3*sqrt(pk)} + n + m) for p-Starforest Editing and O(2^{O(p * sqrt(k) * log(pk))} + n + m) for p-Bicluster Editing. We obtain a similar result for the more general case of t-Partite p-Cluster Editing. This is subexponential in k for a fixed number of clusters, since p is then considered a constant.
  
Our results even out the number of multivariate subexponential time algorithms  and give reasons to believe that this area warrants further study.

Subject Classification

Keywords
  • graph editing
  • subexponential algorithms
  • parameterized complexity

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