MIT Libraries logoDSpace@MIT

MIT
View Item 
  • DSpace@MIT Home
  • MIT Open Access Articles
  • MIT Open Access Articles
  • View Item
  • DSpace@MIT Home
  • MIT Open Access Articles
  • MIT Open Access Articles
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

SETH-Hardness of Coding Problems

Author(s)
Stephens-Davidowitz, Noah; Vaikuntanathan, Vinod
Thumbnail
DownloadAccepted version (613.5Kb)
Open Access Policy

Open Access Policy

Creative Commons Attribution-Noncommercial-Share Alike

Terms of use
Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/
Metadata
Show full item record
Abstract
We show that assuming the strong exponential-Time hypothesis (SETH), there are no non-Trivial algorithms for the nearest codeword problem (NCP), the minimum distance problem (MDP), or the nearest codeword problem with preprocessing (NCPP) on linear codes over any finite field. More precisely, we show that there are no NCP, MDP, or NCPP algorithms running in time q (1-ϵ)n for any constant ϵ>0 for codes with qn codewords. (In the case of NCPP, we assume non-uniform SETH.) We also show that there are no sub-exponential time algorithms for γ-Approximate versions of these problems for some constant γ > 1, under different versions of the exponential-Time hypothesis.
Date issued
2020-01
URI
https://hdl.handle.net/1721.1/130061
Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science; Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Journal
2019 IEEE 60th Annual Symposium on Foundations of Computer Science
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Stephens-Davidowitz, Noah and Vinod Vaikuntanathan. "SETH-Hardness of Coding Problems." 2019 IEEE 60th Annual Symposium on Foundations of Computer Science, November 2019, Baltimore, Maryland, Institute of Electrical and Electronics Engineers, January 2020. © 2019 IEEE
Version: Author's final manuscript
ISBN
9781728149523
9781728149530
ISSN
2575-8454

Collections
  • MIT Open Access Articles

Browse

All of DSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

My Account

Login

Statistics

OA StatisticsStatistics by CountryStatistics by Department
MIT Libraries
PrivacyPermissionsAccessibilityContact us
MIT
Content created by the MIT Libraries, CC BY-NC unless otherwise noted. Notify us about copyright concerns.