Revisiting the Random Subset Sum Problem

Arthur da Cunha, Francesco d'Amore, Frédéric Giroire, Hicham Lesfari, Emanuele Natale, Laurent Viennot

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

2 Citations (Scopus)
185 Downloads (Pure)

Abstract

The average properties of the well-known Subset Sum Problem can be studied by means of its randomised version, where we are given a target value z, random variables X_1, …, X_n, and an error parameter ε > 0, and we seek a subset of the X_is whose sum approximates z up to error ε. In this setup, it has been shown that, under mild assumptions on the distribution of the random variables, a sample of size 𝒪(log(1/ε)) suffices to obtain, with high probability, approximations for all values in [-1/2, 1/2]. Recently, this result has been rediscovered outside the algorithms community, enabling meaningful progress in other fields. In this work, we present an alternative proof for this theorem, with a more direct approach and resourcing to more elementary tools.
Original languageEnglish
Title of host publication31st Annual European Symposium on Algorithms (ESA 2023)
EditorsInge Li Gortz, Martin Farach-Colton, Simon J. Puglisi, Grzegorz Herman
PublisherSchloss Dagstuhl - Leibniz-Zentrum für Informatik
Pages1-11
Number of pages11
ISBN (Electronic)978-3-95977-295-2
DOIs
Publication statusPublished - 30 Aug 2023
MoE publication typeA4 Conference publication
EventEuropean Symposium on Algorithms - Amsterdam, Netherlands
Duration: 4 Sept 20236 Sept 2023
Conference number: 31

Publication series

NameLeibniz International Proceedings in Informatics (LIPIcs)
PublisherSchloss Dagstuhl - Leibniz-Zentrum für Informatik
Volume274
ISSN (Electronic)1868-8969

Conference

ConferenceEuropean Symposium on Algorithms
Abbreviated titleESA
Country/TerritoryNetherlands
CityAmsterdam
Period04/09/202306/09/2023

Keywords

  • Random subset sum
  • Randomised method
  • Subset-sum
  • Combinatorics

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