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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPEW34M/45BP6RE
Repositorysid.inpe.br/sibgrapi/2021/08.30.11.26
Last Update2021:08.30.20.30.21 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2021/08.30.11.26.51
Metadata Last Update2022:06.14.00.00.17 (UTC) administrator
DOI10.1109/SIBGRAPI54419.2021.00049
Citation KeyLevadaHadd:2021:EnLaEi
TitleEntropic Laplacian eigenmaps for unsupervised metric learning
FormatOn-line
Year2021
Access Date2024, May 06
Number of Files1
Size293 KiB
2. Context
Author1 Levada, Alexandre L. M.
2 Haddad, Michel F. C.
Affiliation1 Computing Department, Federal University of São Carlos, Brazil 
2 Department of Land Economy, University of Cambridge and School of Business and Management, Queen Mary University of London, United Kingdom
EditorPaiva, Afonso
Menotti, David
Baranoski, Gladimir V. G.
Proença, Hugo Pedro
Junior, Antonio Lopes Apolinario
Papa, João Paulo
Pagliosa, Paulo
dos Santos, Thiago Oliveira
e Sá, Asla Medeiros
da Silveira, Thiago Lopes Trugillo
Brazil, Emilio Vital
Ponti, Moacir A.
Fernandes, Leandro A. F.
Avila, Sandra
e-Mail Addressalexandre.levada@ufscar.br
Conference NameConference on Graphics, Patterns and Images, 34 (SIBGRAPI)
Conference LocationGramado, RS, Brazil (virtual)
Date18-22 Oct. 2021
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)2021-08-30 20:30:21 :: alexandre.levada@ufscar.br -> administrator :: 2021
2022-03-02 00:54:15 :: administrator -> menottid@gmail.com :: 2021
2022-03-02 13:30:11 :: menottid@gmail.com -> administrator :: 2021
2022-06-14 00:00:17 :: administrator -> :: 2021
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Version Typefinaldraft
KeywordsUnsupervised metric learning
dimensionality reduction
Laplacian Eigenmaps
KL-divergence
manifold learning
AbstractUnsupervised metric learning is concerned with building adaptive distance functions prior to pattern classification. Laplacian eigenmaps consists of a manifold learning algorithm which uses dimensionality reduction to find more compact and meaningful representations of datasets through the Laplacian matrix of graphs. In the present paper, we propose the entropic Laplacian eigenmaps (ELAP) algorithm, a parametric approach that employs the KullbackLeibler (KL-) divergence between patches of the KNN graph instead of the pointwise Euclidean metric as the cost function for the graph weights. Our objective with such a modification is increasing the robustness of Laplacian eigenmaps against noise and outliers. Our results using various real-world datasets indicate that the proposed method is capable of generating more reasonable clusters while reporting greater classification accuracies compared to existing widely adopted methods for dimensionality reduction-based metric learning.
Arrangement 1urlib.net > SDLA > Fonds > SIBGRAPI 2021 > Entropic Laplacian eigenmaps...
Arrangement 2urlib.net > SDLA > Fonds > Full Index > Entropic Laplacian eigenmaps...
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPEW34M/45BP6RE
zipped data URLhttp://urlib.net/zip/8JMKD3MGPEW34M/45BP6RE
Languageen
Target Fileexample.pdf
User Groupalexandre.levada@ufscar.br
Visibilityshown
Update Permissionnot transferred
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPEW34M/45PQ3RS
8JMKD3MGPEW34M/4742MCS
Citing Item Listsid.inpe.br/sibgrapi/2021/11.12.11.46 5
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination 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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