Unsupervised learning: Model-based clustering and learned compression
dc.contributor.author
Tschannen, Michael Tobias
dc.contributor.supervisor
Bölcskei, Helmut
dc.contributor.supervisor
Krause, Andreas
dc.date.accessioned
2019-02-04T11:33:38Z
dc.date.available
2019-02-02T12:06:07Z
dc.date.available
2019-02-04T11:33:38Z
dc.date.issued
2018
dc.identifier.uri
http://hdl.handle.net/20.500.11850/322751
dc.identifier.doi
10.3929/ethz-b-000322751
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.subject
Subspace clustering
en_US
dc.subject
Random processes
en_US
dc.subject
Spectral clustering
en_US
dc.subject
Lossy compression
en_US
dc.subject
Model compression
en_US
dc.subject
Generative modeling
en_US
dc.subject
Deep neural networks
en_US
dc.subject
Generative adversarial networks
en_US
dc.title
Unsupervised learning: Model-based clustering and learned compression
en_US
dc.type
Doctoral Thesis
dc.rights.license
In Copyright - Non-Commercial Use Permitted
dc.date.published
2019-02-04
ethz.size
221 p.
en_US
ethz.code.ddc
DDC - DDC::0 - Computer science, information & general works::004 - Data processing, computer science
ethz.identifier.diss
25498
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::02140 - Dep. Inf.technologie und Elektrotechnik / Dep. of Inform.Technol. Electrical Eng.::03610 - Boelcskei, Helmut / Boelcskei, Helmut
en_US
ethz.date.deposited
2019-02-02T12:06:09Z
ethz.source
FORM
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2019-02-04T11:34:30Z
ethz.rosetta.lastUpdated
2021-02-15T03:33:21Z
ethz.rosetta.versionExported
true
ethz.COinS
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Doctoral Thesis [29937]