Differentially Private Submodular Maximization: Data Summarization in Disguise
dc.contributor.author
Mitrovic, Marko
dc.contributor.author
Bun, Mark
dc.contributor.author
Krause, Andreas
dc.contributor.author
Karbasi, Amin
dc.contributor.editor
Precup, Doina
dc.contributor.editor
Teh, Yee Whye
dc.date.accessioned
2024-07-30T11:37:18Z
dc.date.available
2018-01-29T07:51:31Z
dc.date.available
2018-01-28T15:27:34Z
dc.date.available
2018-01-29T09:12:06Z
dc.date.available
2018-01-29T09:44:08Z
dc.date.available
2024-07-30T11:37:18Z
dc.date.issued
2017
dc.identifier.uri
http://hdl.handle.net/20.500.11850/235819
dc.language.iso
en
en_US
dc.title
Differentially Private Submodular Maximization: Data Summarization in Disguise
en_US
dc.type
Conference Paper
ethz.book.title
Proceedings of Machine Learning Research (PMLR)
en_US
ethz.journal.volume
70
en_US
ethz.pages.start
2478
en_US
ethz.pages.end
2487
en_US
ethz.event
34th International Conference on Machine Learning (ICML 2017)
en_US
ethz.event.location
Sydney, Australia
en_US
ethz.event.date
August 6-11, 2017
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02150 - Dep. Informatik / Dep. of Computer Science::02661 - Institut für Maschinelles Lernen / Institute for Machine Learning::03908 - Krause, Andreas / Krause, Andreas
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02150 - Dep. Informatik / Dep. of Computer Science::02661 - Institut für Maschinelles Lernen / Institute for Machine Learning::03908 - Krause, Andreas / Krause, Andreas
en_US
ethz.relation.isPartOf
https://proceedings.mlr.press/v70/
ethz.date.deposited
2018-01-28T15:27:35Z
ethz.source
FORM
ethz.eth
yes
en_US
ethz.availability
Metadata only
en_US
ethz.rosetta.installDate
2018-01-29T09:12:09Z
ethz.rosetta.lastUpdated
2022-03-28T19:01:47Z
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true
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true
dc.identifier.olduri
http://hdl.handle.net/20.500.11850/235701
dc.identifier.olduri
http://hdl.handle.net/20.500.11850/235777
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Conference Paper [35809]