The Wrong Direction of Jensen’s Inequality Is Algorithmically Right

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Let A be an algorithm with expected running time eX, conditioned on the value of some random variable X. We construct an algorithm A with expected running time O(eE[X]), that fully executes A. In particular, an algorithm whose running time is a random variable T can be converted to one with expected running time O(eE[ln T]), which is never worse than O(E[T]).

Original languageEnglish
Title of host publication50th International Colloquium on Automata, Languages, and Programming, ICALP 2023
EditorsKousha Etessami, Uriel Feige, Gabriele Puppis
ISBN (Electronic)9783959772785
DOIs
StatePublished - Jul 2023
Externally publishedYes
Event50th International Colloquium on Automata, Languages, and Programming, ICALP 2023 - Paderborn, Germany
Duration: 10 Jul 202314 Jul 2023

Publication series

NameLeibniz International Proceedings in Informatics, LIPIcs
Volume261

Conference

Conference50th International Colloquium on Automata, Languages, and Programming, ICALP 2023
Country/TerritoryGermany
CityPaderborn
Period10/07/2314/07/23

Keywords

  • Jensen’s inequality
  • algorithms
  • complexity

All Science Journal Classification (ASJC) codes

  • Software

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