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Lower Bounds for Kernelizations and Other Preprocessing Procedures

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Mathematical Theory and Computational Practice (CiE 2009)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5635))

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Abstract

We first present a method to rule out the existence of strong polynomial kernelizations of parameterized problems under the hypothesis P \(\ne\) NP. This method is applicable, for example, to the problem Sat parameterized by the number of variables of the input formula. Then we obtain improvements of related results in [1,6] by refining the central lemma of their proof method, a lemma due to Fortnow and Santhanam. In particular, assuming that PH \(\ne \Sigma^{\rm {P}}_3\), i.e., that the polynomial hierarchy does not collapse to its third level, we show that every parameterized problem with a “linear OR” and with NP-hard underlying classical problem does not have polynomial reductions to itself that assign to every instance x with parameter k an instance y with |y| = k O(1)·|x|1 − ε (here ε is any given real number greater than zero).

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Chen, Y., Flum, J., Müller, M. (2009). Lower Bounds for Kernelizations and Other Preprocessing Procedures. In: Ambos-Spies, K., Löwe, B., Merkle, W. (eds) Mathematical Theory and Computational Practice. CiE 2009. Lecture Notes in Computer Science, vol 5635. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03073-4_13

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  • DOI: https://doi.org/10.1007/978-3-642-03073-4_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-03072-7

  • Online ISBN: 978-3-642-03073-4

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