License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/DagSemProc.08381.2
URN: urn:nbn:de:0030-drops-17789
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2008/1778/
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Miltersen, Peter Bro ; Reischuk, Rüdiger ; Schnitger, Georg ; van Melkebeek, Dieter

08381 Executive Summary -- Computational Complexity of Discrete Problems

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08381.SWM.1778.pdf (0.1 MB)

Abstract

Estimating the computational complexity of discrete problems constitutes one of the central and classical topics in the theory of computation. Mathematicians and computer scientists have long tried to classify natural families of Boolean relations according to fundamental complexity measures like time and space, both in the uniform and in the nonuniform setting. Several models of computation have been developed in order to capture the various capabilities of digital computing devices, including parallelism, randomness, and quantum interference.

BibTeX - Entry

@InProceedings{miltersen_et_al:DagSemProc.08381.2,
  author =	{Miltersen, Peter Bro and Reischuk, R\"{u}diger and Schnitger, Georg and van Melkebeek, Dieter},
  title =	{{08381 Executive Summary – Computational Complexity of Discrete Problems}},
  booktitle =	{Computational Complexity of Discrete Problems},
  pages =	{1--7},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2008},
  volume =	{8381},
  editor =	{Peter Bro Miltersen and R\"{u}diger Reischuk and Georg Schnitger and Dieter van Melkebeek},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2008/1778},
  URN =		{urn:nbn:de:0030-drops-17789},
  doi =		{10.4230/DagSemProc.08381.2},
  annote =	{Keywords: Computational complexity, discrete problems, Turing machines, circuits, proof complexity, pseudorandomness, derandomization, cryptography, computational learning, communication complexity, query complexity, hardness of approximation}
}

Keywords: Computational complexity, discrete problems, Turing machines, circuits, proof complexity, pseudorandomness, derandomization, cryptography,
Freie Schlagwörter (englisch): computational learning, communication complexity, query complexity, hardness of approximation
Collection: 08381 - Computational Complexity of Discrete Problems
Issue Date: 2008
Date of publication: 11.12.2008

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