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Coding Theory in the Time of Big Data (Dagstuhl Seminar 16321)
Authors and all authors of the abstracts in this report
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Part of:
Issue:
Dagstuhl Reports, Volume 6, Issue 8
Volume: Dagstuhl Reports, Volume 6
Journal: Dagstuhl Reports (DagRep) - License:
Creative Commons Attribution 3.0 Unported license
- Publication date: 2016-12-09
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Martin Bossert, Eimear Byrne, and Emina Soljanin. Coding Theory in the Time of Big Data (Dagstuhl Seminar 16321). In Dagstuhl Reports, Volume 6, Issue 8, pp. 1-20, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2016)
https://doi.org/10.4230/DagRep.6.8.1
https://doi.org/10.4230/DagRep.6.8.1
Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 16321 "Coding Theory in the Time of Big Data". The overarching technical theme was on how fundamentals of coding theory could be applied to data storage and transmission in the context of big data and conversely, on new problems in coding theory arising from such applications.
Keywords
- Algebraic coding theory
- Caching problems
- Coding theory
- Complexity theory
- Cryptography
- Distributed storage
- Error-correction
- Index coding
- Information theory
- Randomized algorithms
- Streaming algorithms
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