Publication:

Margin-Based Training of HDC Classifiers

Date

2025
Journal article
https://doi.org/10.3390/bdcc9030068
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cris.virtual.orcid0000-0002-5353-9953
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dc.contributor.authorSmets, Laura
dc.contributor.authorRachkovskij, Dmitri
dc.contributor.authorOsipov, Evgeny
dc.contributor.authorVan Leekwijck, Werner
dc.contributor.authorVolkov, Olexander
dc.contributor.authorLatre, Steven
dc.contributor.imecauthorSmets, Laura
dc.contributor.imecauthorVan Leekwijck, Werner
dc.contributor.imecauthorLatre, Steven
dc.contributor.orcidimecSmets, Laura::0000-0002-5353-9953
dc.contributor.orcidimecVan Leekwijck, Werner::0000-0002-2956-2889
dc.contributor.orcidimecLatre, Steven::0000-0003-0351-1714
dc.date.accessioned2025-04-29T13:11:59Z
dc.date.available2025-04-03T04:34:52Z
dc.date.available2025-04-29T13:11:59Z
dc.date.issued2025
dc.description.wosFundingTextThe work of L.S. and W.V.L. was supported by the Flemish Government under the "Onderzoeksprogramma Artificiele Intelligentie (AI) Vlaanderen" program. The work of D.R. was supported in part by the Swedish Foundation for Strategic Research (SSF, grant nos. UKR22-0024, UKR24-0014), the Swedish Research Council (VR) Scholars at Risk (SAR) Sweden (VR SAR grant no. GU 2022/1963), the National Research Fund of Ukraine (NRFU, grant no. 2023.04/0082), and LTU support grant. The work of E.O. was supported in part by the Swedish Research Council (VR grant no. 2022-04657). E.O. and D.R. acknowledge the computational resources provided by the National Academic Infrastructure for Supercomputing in Sweden (NAISS), partially funded by the Swedish Research Council through grant agreement no. 2022-06725, as well as help and support of Denis Kleyko and Philip Gard.
dc.identifier.doi10.3390/bdcc9030068
dc.identifier.issn2504-2289
dc.identifier.urihttps://imec-publications.be/handle/20.500.12860/45484
dc.publisherMDPI
dc.source.beginpage68
dc.source.issue3
dc.source.journalBIG DATA AND COGNITIVE COMPUTING
dc.source.numberofpages22
dc.source.volume9
dc.subject.disciplineComputer science/information technology
dc.subject.keywordsCLASSIFICATION
dc.subject.keywordsRECOGNITION
dc.title

Margin-Based Training of HDC Classifiers

dc.typeJournal article
dspace.entity.typePublication
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