TY - GEN
T1 - Online kernel-based classification by projections
AU - Slavakis, Konstantinos
AU - Theodoridis, Sergios
AU - Yamada, Isao
PY - 2007/8/6
Y1 - 2007/8/6
N2 - The goal of this paper is the development of a novel efficient online kernel-based algorithm for classification. The spirit of the algorithm stems from the recently introduced Adaptive Projected Subgradient Method. This is a general convex analytic tool that employs projections onto a sequence of convex sets and it can be considered as a generalization of the celebrated APA algorithm, widely used in classical adaptive filtering.
AB - The goal of this paper is the development of a novel efficient online kernel-based algorithm for classification. The spirit of the algorithm stems from the recently introduced Adaptive Projected Subgradient Method. This is a general convex analytic tool that employs projections onto a sequence of convex sets and it can be considered as a generalization of the celebrated APA algorithm, widely used in classical adaptive filtering.
KW - Adaptive systems
KW - Pattern classification
UR - http://www.scopus.com/inward/record.url?scp=34547540580&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=34547540580&partnerID=8YFLogxK
U2 - 10.1109/ICASSP.2007.366263
DO - 10.1109/ICASSP.2007.366263
M3 - Conference contribution
AN - SCOPUS:34547540580
SN - 1424407281
SN - 9781424407286
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
BT - 2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07
T2 - 2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07
Y2 - 15 April 2007 through 20 April 2007
ER -