License: 
Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/OASIcs.SOSA.2019.18
URN: urn:nbn:de:0030-drops-100447
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2018/10044/
Liu, Paul ;
Vondrak, Jan
Submodular Optimization in the MapReduce Model
Abstract
Submodular optimization has received significant attention in both practice and theory, as a wide array of problems in machine learning, auction theory, and combinatorial optimization have submodular structure. In practice, these problems often involve large amounts of data, and must be solved in a distributed way. One popular framework for running such distributed algorithms is MapReduce. In this paper, we present two simple algorithms for cardinality constrained submodular optimization in the MapReduce model: the first is a (1/2-o(1))-approximation in 2 MapReduce rounds, and the second is a (1-1/e-epsilon)-approximation in (1+o(1))/epsilon MapReduce rounds.
BibTeX - Entry
@InProceedings{liu_et_al:OASIcs:2018:10044,
author = {Paul Liu and Jan Vondrak},
title = {{Submodular Optimization in the MapReduce Model}},
booktitle = {2nd Symposium on Simplicity in Algorithms (SOSA 2019)},
pages = {18:1--18:10},
series = {OpenAccess Series in Informatics (OASIcs)},
ISBN = {978-3-95977-099-6},
ISSN = {2190-6807},
year = {2018},
volume = {69},
editor = {Jeremy T. Fineman and Michael Mitzenmacher},
publisher = {Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
address = {Dagstuhl, Germany},
URL = {http://drops.dagstuhl.de/opus/volltexte/2018/10044},
URN = {urn:nbn:de:0030-drops-100447},
doi = {10.4230/OASIcs.SOSA.2019.18},
annote = {Keywords: mapreduce, submodular, optimization, approximation algorithms}
}
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Keywords: |
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mapreduce, submodular, optimization, approximation algorithms |
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Collection: |
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2nd Symposium on Simplicity in Algorithms (SOSA 2019) |
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Issue Date: |
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2018 |
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Date of publication: |
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08.01.2019 |
