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International Symposium on Parameterized and Exact Computation

IPEC 2014: Parameterized and Exact Computation pp 1–14Cite as

Lower Bounds for Kernelization

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,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 \(coNP \not \subseteq NP/poly\).

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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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Authors and Affiliations

  1. Department of Information and Computing Science, Utrecht University, P.O. Box 80.089, 3508 TB, Utrecht, The Netherlands

    Hans L. Bodlaender

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  1. Hans L. Bodlaender
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Correspondence to Hans L. Bodlaender .

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Editors and Affiliations

  1. Faculty of Mathematics, Informatics and Mechanics, University of Warsaw, Warsaw, Poland

    Marek Cygan

  2. University of Bergen, Bergen, Norway

    Pinar Heggernes

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Bodlaender, H.L. (2014). Lower Bounds for Kernelization. In: Cygan, M., Heggernes, P. (eds) Parameterized and Exact Computation. IPEC 2014. Lecture Notes in Computer Science(), vol 8894. Springer, Cham. https://doi.org/10.1007/978-3-319-13524-3_1

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  • DOI: https://doi.org/10.1007/978-3-319-13524-3_1

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  • Online ISBN: 978-3-319-13524-3

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