Conference paper Open Access

AKSDA-MSVM: A GPU-accelerated Multiclass Learning Framework for Multimedia

Arestis-Chartampilas, Stavros; Gkalelis, Nikolaos; Mezaris,Vasileios


Dublin Core Export

<?xml version='1.0' encoding='utf-8'?>
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:creator>Arestis-Chartampilas, Stavros</dc:creator>
  <dc:creator>Gkalelis, Nikolaos</dc:creator>
  <dc:creator>Mezaris,Vasileios</dc:creator>
  <dc:date>2016-10-17</dc:date>
  <dc:description>In this paper, a combined nonlinear dimensionality reduction and multiclass classification framework is proposed. Specifically, a novel discriminant analysis (DA) technique, called accelerated kernel subclass discriminant analysis (AKSDA), derives a discriminant subspace, and a linear multiclass support vector machine (MSVM) computes a set of separating hyperplanes in the derived subspace. Moreover, within this framework an approach for accelerating the computation of multiple Gram matrices and an associated late fusion scheme are presented. Experimental evaluation in five multimedia datasets, on tasks such as video event detection and news document classification, shows that the proposed framework achieves excellent results in terms of both training time and generalization performance.</dc:description>
  <dc:identifier>https://zenodo.org/record/162405</dc:identifier>
  <dc:identifier>10.1145/2964284.2967263</dc:identifier>
  <dc:identifier>oai:zenodo.org:162405</dc:identifier>
  <dc:relation>info:eu-repo/grantAgreement/EC/FP7/600826/</dc:relation>
  <dc:relation>info:eu-repo/grantAgreement/EC/H2020/687786/</dc:relation>
  <dc:relation>url:https://zenodo.org/communities/ecfunded</dc:relation>
  <dc:relation>url:https://zenodo.org/communities/invid-h2020</dc:relation>
  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:rights>http://creativecommons.org/licenses/by/4.0/legalcode</dc:rights>
  <dc:subject>Discriminant analysis; GPU; multiclass classification; SVM</dc:subject>
  <dc:title>AKSDA-MSVM: A GPU-accelerated Multiclass Learning Framework for Multimedia</dc:title>
  <dc:type>info:eu-repo/semantics/conferencePaper</dc:type>
  <dc:type>publication-conferencepaper</dc:type>
</oai_dc:dc>
93
36
views
downloads
Views 93
Downloads 36
Data volume 22.5 MB
Unique views 88
Unique downloads 36

Share

Cite as