A Retrospective on (Meta) Kernelization

Dimitrios M. Thilikos

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

In parameterized complexity, a kernelization algorithm can be seen as a reduction of a parameterized problem to itself, so that the produced equivalent instance has size depending exclusively on the parameter. If this size is polynomial, then we say that the parameterized problem in question admits a polynomial kernelization algorithm. Kernelization can be seen as a formalization of the notion of preprocessing and has occupied a big part of the research on Multi-variate Algorithmics. The first algorithmic meta-theorem on kernelization appeared in [14] and unified a large family of previously known kernelization results on problems defined on topologically embeddable graphs. In this exposition we present the central results of this paper. During our presentation we pay attention to the abstractions on which the results where founded and take into account the subsequent advancements on this topic.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer
Pages222-246
Number of pages25
DOIs
StatePublished - 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12160 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Keywords

  • Algorithmic meta-theorems finite index
  • Bidimensionality
  • Finite integer index
  • Kernelization algorithms
  • Monadic Second Order Logic
  • Parameterized algorithms
  • Parameterized problems
  • Protrusion decompositions
  • Separability
  • Treewidth

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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