Abstract
Kernelization is a mathematical framework for the study of polynomial time pre-processing. Over the last few years Kernelization has received considerable attention. In this talk I will survey the recent developments in the field, and highlight some of the interesting research directions.
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References
Bodlaender, H.L., Downey, R.G., Fellows, M.R., Hermelin, D.: On problems without polynomial kernels. J. Comput. Syst. Sci. 75(8), 423–434 (2009)
Downey, R.G., Fellows, M.R.: Parameterized complexity. Springer, New York (1999)
Flum, J., Grohe, M.: Parameterized Complexity Theory. Springer, Berlin (2006)
Fortnow, L., Santhanam, R.: Infeasibility of instance compression and succinct pcps for np. In: STOC, pp. 133–142 (2008)
Niedermeier, R.: Invitation to fixed-parameter algorithms. Oxford University Press, Oxford (2006)
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Lokshtanov, D. (2011). Kernelization: An Overview. In: Owe, O., Steffen, M., Telle, J.A. (eds) Fundamentals of Computation Theory. FCT 2011. Lecture Notes in Computer Science, vol 6914. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22953-4_3
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DOI: https://doi.org/10.1007/978-3-642-22953-4_3
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