Provable Non-Convex Optimization and Algorithm Validation via Submodularity
dc.contributor.author
Bian, Yatao
dc.contributor.supervisor
Buhman, Joachim M.
dc.contributor.supervisor
Krause, Andreas
dc.contributor.supervisor
Yue, Yisong
dc.date.accessioned
2020-03-30T08:47:48Z
dc.date.available
2019-12-17T15:48:26Z
dc.date.available
2019-12-18T08:34:20Z
dc.date.available
2019-12-18T08:38:42Z
dc.date.available
2020-03-30T08:47:48Z
dc.date.issued
2019
dc.identifier.uri
http://hdl.handle.net/20.500.11850/386316
dc.identifier.doi
10.3929/ethz-b-000386316
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
ETH Zurich
en_US
dc.rights.uri
http://rightsstatements.org/page/InC-NC/1.0/
dc.title
Provable Non-Convex Optimization and Algorithm Validation via Submodularity
en_US
dc.type
Doctoral Thesis
dc.rights.license
In Copyright - Non-Commercial Use Permitted
dc.date.published
2019-12-18
ethz.size
220 p.
en_US
ethz.code.ddc
DDC - DDC::0 - Computer science, information & general works::004 - Data processing, computer science
en_US
ethz.identifier.diss
26496
en_US
ethz.publication.place
Zurich
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::03659 - Buhmann, Joachim M. / Buhmann, Joachim M.
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::03659 - Buhmann, Joachim M. / Buhmann, Joachim M.
en_US
ethz.date.deposited
2019-12-17T15:48:36Z
ethz.source
FORM
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2019-12-18T08:34:34Z
ethz.rosetta.lastUpdated
2022-03-29T01:40:27Z
ethz.rosetta.versionExported
true
ethz.COinS
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Doctoral Thesis [28830]