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Lower Bounds for Kernelization

  • Hans L. BodlaenderEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8894)

Abstract

Kernelization is the process of transforming the input of a combinatorial decision problem to an equivalent instance, with a guarantee on the size of the resulting instances as a function of a parameter. Recent techniques from the field of fixed parameter complexity and tractability allow to give lower bounds for such kernels. In particular, it is discussed how one can show for parameterized problems that these do not have polynomial kernels, under the assumption that \(coNP \not \subseteq NP/poly\).

Notes

Acknowledgments

This survey would not have been possible without the discussions and cooperation with several collegues: Rod Downey, Mike Fellows, Bart Jansen, Danny Hermelin, Stefan Kratsch, Stéphan Thomassé and Andres Yeo. Thank you very much! I apologize to all whose work was inadvertingly or due to space was not or insufficiently discussed here.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Department of Information and Computing ScienceUtrecht UniversityUtrechtThe Netherlands

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