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dc.contributor.author
Thély, Maxime
dc.contributor.author
Sutter, Tobias
dc.contributor.author
Esfahani, Peyman M.
dc.contributor.author
Lygeros, John
dc.contributor.editor
Dochain, Denis
dc.contributor.editor
Henrion, Didier
dc.contributor.editor
Peaucelle, Dimitri
dc.date.accessioned
2021-07-28T05:35:30Z
dc.date.available
2018-01-23T12:21:05Z
dc.date.available
2018-01-23T11:41:05Z
dc.date.available
2017-10-29T02:40:51Z
dc.date.available
2017-11-29T13:54:48Z
dc.date.available
2018-01-22T11:04:14Z
dc.date.available
2018-01-23T11:38:56Z
dc.date.available
2018-08-31T12:35:33Z
dc.date.available
2021-07-28T05:35:30Z
dc.date.issued
2017-07
dc.identifier.issn
2405-8963
dc.identifier.other
10.1016/j.ifacol.2017.08.1977
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/234334
dc.description.abstract
We present an approximation method to a class of parametric integration problems that naturally appear when solving the dual of the maximum entropy estimation problem. Our method builds up on a recent generalization of Gauss quadratures via an infinite-dimensional linear program, and utilizes a convex clustering algorithm to compute an approximate solution which requires reduced computational effort. It shows to be particularly appealing when looking at problems with unusual domains and in a multi-dimensional setting. As a proof of concept we apply our method to an example problem on the unit disc.
en_US
dc.language.iso
en
en_US
dc.publisher
Elsevier
en_US
dc.subject
Entropy maximization
en_US
dc.subject
convex clustering
en_US
dc.subject
linear programming
en_US
dc.subject
importance sampling
en_US
dc.title
Maximum entropy estimation via Gauss-LP Quadratures
en_US
dc.type
Conference Paper
dc.date.published
2017-10-18
ethz.book.title
20th IFAC World Congress. Proceedings
en_US
ethz.journal.title
IFAC-PapersOnLine
ethz.journal.volume
50
en_US
ethz.journal.issue
1
en_US
ethz.pages.start
10470
en_US
ethz.pages.end
10475
en_US
ethz.event
20th IFAC World Congress (IFAC 2017)
en_US
ethz.event.location
Toulouse, France
en_US
ethz.event.date
July 9-14, 2017
en_US
ethz.identifier.scopus
ethz.publication.place
Kidlington
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.::02650 - Institut für Automatik / Automatic Control Laboratory::03751 - Lygeros, John / Lygeros, John
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02140 - Dep. Inf.technologie und Elektrotechnik / Dep. of Inform.Technol. Electrical Eng.::02650 - Institut für Automatik / Automatic Control Laboratory::03751 - Lygeros, John / Lygeros, John
ethz.date.deposited
2017-10-29T02:40:55Z
ethz.source
SCOPUS
ethz.source
BATCH
ethz.eth
yes
en_US
ethz.availability
Metadata only
en_US
ethz.rosetta.installDate
2018-01-25T10:52:13Z
ethz.rosetta.lastUpdated
2022-03-29T10:44:52Z
ethz.rosetta.versionExported
true
dc.identifier.olduri
http://hdl.handle.net/20.500.11850/232153
dc.identifier.olduri
http://hdl.handle.net/20.500.11850/202013
ethz.COinS
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