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DOI: 10.4230/DagRep.7.4.1
URN: urn:nbn:de:0030-drops-75452
URL: http://drops.dagstuhl.de/opus/volltexte/2017/7545/
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Manthey, Bodo ; Mathieu, Claire ; Röglin, Heiko ; Upfal, Eli
Weitere Beteiligte (Hrsg. etc.): Bodo Manthey and Claire Mathieu and Heiko Röglin and Eli Upfal

Probabilistic Methods in the Design and Analysis of Algorithms (Dagstuhl Seminar 17141)

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dagrep_v007_i004_p001_s17141.pdf (2 MB)


Abstract

This report documents the program and the outcomes of Dagstuhl Seminar 17141 "Probabilistic Methods in the Design and Analysis of Algorithms". Probabilistic methods play a central role in theoretical computer science. They are a powerful and widely applied tool used, for example, for designing efficient randomized algorithms and for establishing various lower bounds in complexity theory. They also form the basis of frameworks like average-case and smoothed analysis, in which algorithms are analyzed beyond the classical worst-case perspective. The seminar was on probabilistic methods with a focus on the design and analysis of algorithms. The seminar helped to consolidate the research and to foster collaborations among the researchers who use probabilistic methods in different areas of the design and analysis of algorithms.

BibTeX - Entry

@Article{manthey_et_al:DR:2017:7545,
  author =	{Bodo Manthey and Claire Mathieu and Heiko R{\"o}glin and Eli Upfal},
  title =	{{Probabilistic Methods in the Design and Analysis of Algorithms (Dagstuhl Seminar 17141)}},
  pages =	{1--22},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2017},
  volume =	{7},
  number =	{4},
  editor =	{Bodo Manthey and Claire Mathieu and Heiko R{\"o}glin and Eli Upfal},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2017/7545},
  URN =		{urn:nbn:de:0030-drops-75452},
  doi =		{10.4230/DagRep.7.4.1},
  annote =	{Keywords: analysis of algorithms, average-case analysis, random graphs, randomized algorithms, smoothed analysis, sub-linear algorithms}
}

Keywords: analysis of algorithms, average-case analysis, random graphs, randomized algorithms, smoothed analysis, sub-linear algorithms
Seminar: Dagstuhl Reports, Volume 7, Issue 4
Issue Date: 2017
Date of publication: 19.12.2017


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