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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPBW34M/3A32SLE
Repositorysid.inpe.br/sibgrapi/2011/07.06.23.53
Last Update2011:07.06.23.53.51 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2011/07.06.23.53.51
Metadata Last Update2022:06.14.00.07.08 (UTC) administrator
DOI10.1109/SIBGRAPI.2011.21
Citation KeyRauberBern:2011:KeMuPe
TitleKernel Multilayer Perceptron
FormatDVD, On-line.
Year2011
Access Date2024, Apr. 30
Number of Files1
Size154 KiB
2. Context
Author1 Rauber, Thomas W.
2 Berns, Karsten
Affiliation1 Departamento de Informática, Centro Tecnológico, Universidade Federal do Espírito Santo
2 Robotics Research Lab, Department of Computer Science, University of Kaiserslautern, Gottlieb-Daimler-Strasse, 67663 Kaiserslautern, Germany
EditorLewiner, Thomas
Torres, Ricardo
e-Mail Addressthomas@inf.ufes.br
Conference NameConference on Graphics, Patterns and Images, 24 (SIBGRAPI)
Conference LocationMaceió, AL, Brazil
Date28-31 Aug. 2011
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)2011-07-23 15:36:12 :: thomas@inf.ufes.br -> administrator :: 2011
2022-06-14 00:07:08 :: administrator -> :: 2011
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Version Typefinaldraft
KeywordsMultilayer Perceptron
kernel mapping
AbstractWe enhance the Multilayer Perceptron to map a feature vector not only from the original d-dimensional feature space, but from an intermediate implicit Hilbert feature space in which kernels calculate inner products. The kernel substitutes the usual inner product between weight vectors and the input vector (or the feature vector of the hidden layer). The objective is to boost the generalization capability of this universal function approximator even more. Classification experiments with standard Machine Learning data sets are shown. We are able to improve the classification accuracy performance criterion for certain kernel types and their intrinsic parameters for the majority of the data sets.
Arrangement 1urlib.net > SDLA > Fonds > SIBGRAPI 2011 > Kernel Multilayer Perceptron
Arrangement 2urlib.net > SDLA > Fonds > Full Index > Kernel Multilayer Perceptron
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Content
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPBW34M/3A32SLE
zipped data URLhttp://urlib.net/zip/8JMKD3MGPBW34M/3A32SLE
Languageen
Target File86589.pdf
User Groupthomas@inf.ufes.br
Visibilityshown
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPEW34M/46SKNPE
8JMKD3MGPEW34M/4742MCS
Citing Item Listsid.inpe.br/sibgrapi/2022/05.15.00.56 4
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination documentstage edition electronicmailaddress group isbn issn label lineage mark nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder schedulinginformation secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url volume


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