Improved deterministic algorithms for linear programming in low dimensions

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

At SODA'93, Chazelle and Matousek presented a derandom-ization of Clarkson's sampling-based algorithm [FOCS'88] for solving linear programs with n constraints and d variables in d(7+o(1))dn deterministic time. The time bound can be improved to d(5+o)(1)dn with subsequent work by Bronnimann, Chazelle, and Matousek [FOCS'93l. We first point out a much simpler derandomization of Clarkson's algorithm that avoids ϵ-approximations and runs in d(3+o(1))dn time. We then describe a few additional ideas that eventually improve the deterministic time bound to d(1/2+o(1))dn.

Original languageEnglish (US)
Title of host publication27th Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2016
EditorsRobert Krauthgamer
PublisherAssociation for Computing Machinery
Pages1213-1219
Number of pages7
ISBN (Electronic)9781510819672
DOIs
StatePublished - 2016
Externally publishedYes
Event27th Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2016 - Arlington, United States
Duration: Jan 10 2016Jan 12 2016

Publication series

NameProceedings of the Annual ACM-SIAM Symposium on Discrete Algorithms
Volume2

Other

Other27th Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2016
Country/TerritoryUnited States
CityArlington
Period1/10/161/12/16

ASJC Scopus subject areas

  • Software
  • Mathematics(all)

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