Cluster editing with locally bounded modifications revisited
Paper i proceeding, 2013

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.

cluster editing

kernelization

edit degree

list edge coloring

Författare

Peter Damaschke

Chalmers, Data- och informationsteknik, Datavetenskap

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

03029743 (ISSN) 16113349 (eISSN)

Vol. 8288 LNCS 433-437

Ämneskategorier

Beräkningsmatematik

Diskret matematik

Fundament

Grundläggande vetenskaper

DOI

10.1007/978-3-642-45278-9_38

Mer information

Senast uppdaterat

2024-11-14