TY - GEN
T1 - Effects of norms on learning properties of support vector machines
AU - Ikeda, Kazushi
AU - Murata, Noboru
PY - 2005/1/1
Y1 - 2005/1/1
N2 - Support Vector Machines (SVMs) are known to have a high generalization ability, yet a heavy computational load since margin maximization results in a quadratic programming problem. It is known that this maximization task results in a pth-order programming problem if we employ the Lp norm instead of the L2 norm. In this paper, we theoretically show the effects of p on the learning properties of SVMs by clarifying its geometrical meaning.
AB - Support Vector Machines (SVMs) are known to have a high generalization ability, yet a heavy computational load since margin maximization results in a quadratic programming problem. It is known that this maximization task results in a pth-order programming problem if we employ the Lp norm instead of the L2 norm. In this paper, we theoretically show the effects of p on the learning properties of SVMs by clarifying its geometrical meaning.
UR - http://www.scopus.com/inward/record.url?scp=33646760980&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=33646760980&partnerID=8YFLogxK
U2 - 10.1109/ICASSP.2005.1416285
DO - 10.1109/ICASSP.2005.1416285
M3 - Conference contribution
AN - SCOPUS:33646760980
SN - 0780388747
SN - 9780780388741
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - V241-V244
BT - 2005 IEEE ICASSP '05 - Proc. - Design and Implementation of Signal Proces.Syst.,Indust. Technol. Track,Machine Learning for Signal Proces. Education, Spec. Sessions
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05
Y2 - 18 March 2005 through 23 March 2005
ER -