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 language | English |
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Title of host publication | 31st Annual European Symposium on Algorithms (ESA 2023) |
Editors | Inge Li Gortz, Martin Farach-Colton, Simon J. Puglisi, Grzegorz Herman |
Publisher | Schloss Dagstuhl - Leibniz-Zentrum für Informatik |
Pages | 1-11 |
Number of pages | 11 |
ISBN (Electronic) | 978-3-95977-295-2 |
DOIs | |
Publication status | Published - 30 Aug 2023 |
MoE publication type | A4 Conference publication |
Event | European Symposium on Algorithms - Amsterdam, Netherlands Duration: 4 Sept 2023 → 6 Sept 2023 Conference number: 31 |
Publication series
Name | Leibniz International Proceedings in Informatics (LIPIcs) |
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Publisher | Schloss Dagstuhl - Leibniz-Zentrum für Informatik |
Volume | 274 |
ISSN (Electronic) | 1868-8969 |
Conference
Conference | European Symposium on Algorithms |
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Abbreviated title | ESA |
Country/Territory | Netherlands |
City | Amsterdam |
Period | 04/09/2023 → 06/09/2023 |
Keywords
- Random subset sum
- Randomised method
- Subset-sum
- Combinatorics