162405
doi
10.1145/2964284.2967263
oai:zenodo.org:162405
user-invid-h2020
user-eu
Gkalelis, Nikolaos
CERTH
Mezaris,Vasileios
CERTH
AKSDA-MSVM: A GPU-accelerated Multiclass Learning Framework for Multimedia
Arestis-Chartampilas, Stavros
CERTH
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
Discriminant analysis; GPU; multiclass classification; SVM
<p>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.</p>
Zenodo
2016-10-17
info:eu-repo/semantics/conferencePaper
657267
user-invid-h2020
user-eu
award_title=Concise Preservation by combining Managed Forgetting and Contextualized Remembering; award_number=600826; award_identifiers_scheme=url; award_identifiers_identifier=https://cordis.europa.eu/projects/600826; funder_id=00k4n6c32; funder_name=European Commission;
award_title=In Video Veritas – Verification of Social Media Video Content for the News Industry; award_number=687786; award_identifiers_scheme=url; award_identifiers_identifier=https://cordis.europa.eu/projects/687786; funder_id=00k4n6c32; funder_name=European Commission;
1579542123.399965
625709
md5:d4eeabd1d893c25a3b9aabfae944706e
https://zenodo.org/records/162405/files/mm16_2_preprint.pdf
public