A probabilistic approach to problems parameterized above or below tight bounds

  • Gregory Gutin
  • , Eun Jung Kim
  • , Stefan Szeider
  • , Anders Yeo

Research output: Contribution to journalArticlepeer-review

31 Citations (Scopus)

Abstract

We introduce a new approach for establishing fixed-parameter tractability of problems parameterized above tight lower bounds or below tight upper bounds. To illustrate the approach we consider two problems of this type of unknown complexity that were introduced by Mahajan, Raman and Sikdar [M. Mahajan, V. Raman, S. Sikdar, Parameterizing above or below guaranteed values, J. Comput. System Sci. 75 (2) (2009) 137-153]. We show that a generalization of one of the problems and three non-trivial special cases of the other problem admit kernels of quadratic size. As a byproduct we obtain a new probabilistic inequality that could be of independent interest. Our new inequality is dual to the Hypercontractive Inequality.

Original languageEnglish
Pages (from-to)422-429
Number of pages8
JournalJournal of Computer and System Sciences
Volume77
Issue number2
DOIs
Publication statusPublished - Mar 2011
Externally publishedYes

Keywords

  • Above tight bounds
  • Fixed-parameter tractable
  • Hypercontractive Inequality
  • Kernel
  • Parameterized problems
  • Probabilistic method

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Networks and Communications
  • Computational Theory and Mathematics
  • Applied Mathematics

Fingerprint

Dive into the research topics of 'A probabilistic approach to problems parameterized above or below tight bounds'. Together they form a unique fingerprint.

Cite this