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dc.contributor.author
Gehler, Peter
dc.contributor.author
Schölkopf, Bernhard
dc.contributor.editor
Camps-Valls, Gustavo
dc.contributor.editor
Bruzzone, Lorenzo
dc.date.accessioned
2017-06-14T10:18:44Z
dc.date.available
2017-06-14T10:18:44Z
dc.date.issued
2009-10-23
dc.identifier.isbn
978-0-470-72211-4
dc.identifier.other
10.1002/9780470748992.ch2
dc.identifier.uri
http://hdl.handle.net/20.500.11850/156677
dc.language.iso
en
dc.publisher
Wiley
dc.subject
kernel learning algorithms - standard tool in area of machine learning and pattern recognition
dc.subject
measuring similarity with kernels
dc.subject
reproducing kernel Hilbert space (RKHS) and reproducing property of kernel
dc.subject
operations in RKHS
dc.subject
kernel construction
dc.subject
homogeneous polynomial kernel
dc.subject
spatial kernel for image processing
dc.subject
representer theorem
dc.subject
learning with kernels
dc.subject
kernel principal component analysis (PCA)
dc.title
An introduction to kernel-based learning algorithms
dc.type
Book Chapter
ethz.book.title
Kernel methods for remote sensing data analysis
ethz.pages.start
25
ethz.pages.end
48
ethz.version.edition
1., Auflage
ethz.notes
Abstract not available. Published Online 4 November 2009.
ethz.publication.place
New York, NY
ethz.publication.status
published
ethz.date.deposited
2017-06-14T10:23:40Z
ethz.source
ECIT
ethz.identifier.importid
imp59364cd8b031c75737
ethz.ecitpid
pub:34903
ethz.eth
yes
ethz.availability
Metadata only
ethz.rosetta.installDate
2017-07-14T17:11:08Z
ethz.rosetta.lastUpdated
2017-07-14T17:11:08Z
ethz.rosetta.versionExported
true
ethz.COinS
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