Fast and Provably Good Seedings for k-Means
dc.contributor.author
Bachem, Olivier
dc.contributor.author
Lucic, Mario
dc.contributor.author
Hassani, Hamed
dc.contributor.author
Krause, Andreas
dc.contributor.editor
Lee, Daniel D.
dc.contributor.editor
von Luxburg, Ulrike
dc.contributor.editor
Garnett, Roman
dc.contributor.editor
Sugiyama, Masashi
dc.contributor.editor
Guyon, Isabelle
dc.date.accessioned
2018-10-25T07:15:16Z
dc.date.available
2017-06-12T13:40:39Z
dc.date.available
2018-10-25T07:15:16Z
dc.date.issued
2016
dc.identifier.isbn
978-1-5108-3881-9
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/121220
dc.language.iso
en
en_US
dc.publisher
Curran
dc.title
Fast and Provably Good Seedings for k-Means
en_US
dc.type
Conference Paper
ethz.book.title
Neural Information Processing Systems. Annual Conference 30th 2016, (7 Vols) Advances In Neural Information Processing Systems 29
en_US
ethz.pages.start
55
en_US
ethz.pages.end
63
en_US
ethz.event
30th Annual Conference on Neural Information Processing (NIPS 2016)
en_US
ethz.event.location
Barcelona, Spain
ethz.event.date
December 4 - December 9, 2016
en_US
ethz.publication.place
Red Hook, NY
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
ethz.identifier.url
https://papers.nips.cc/paper/6478-fast-and-provably-good-seedings-for-k-means
ethz.date.deposited
2017-06-12T13:45:00Z
ethz.source
ECIT
ethz.identifier.importid
imp593654c28cddc33082
ethz.ecitpid
pub:183314
ethz.eth
yes
en_US
ethz.availability
Metadata only
en_US
ethz.rosetta.installDate
2018-10-25T07:15:21Z
ethz.rosetta.lastUpdated
2024-02-02T06:27:13Z
ethz.rosetta.versionExported
true
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Publikationstyp
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Conference Paper [34982]