Abstract
For Cluster Editing where both the number of clusters and the edit degree are bounded, we speed up the kernelization by almost a factor n compared to Komusiewicz and Uhlmann (2012), at cost of a marginally worse kernel size bound. We also give sufficient conditions for a subset of vertices to be a cluster in some optimal clustering.
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Damaschke, P. (2013). Cluster Editing with Locally Bounded Modifications Revisited. In: Lecroq, T., Mouchard, L. (eds) Combinatorial Algorithms. IWOCA 2013. Lecture Notes in Computer Science, vol 8288. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-45278-9_38
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DOI: https://doi.org/10.1007/978-3-642-45278-9_38
Publisher Name: Springer, Berlin, Heidelberg
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