TY - GEN
T1 - Invariant feature extraction and classification in kernel spaces
AU - Mika, Sebastian
AU - Rätsch, Gunnar
AU - Weston, Jason
AU - Schölkopf, Bernhard
AU - Smola, Alex
AU - Müller, Klaus Robert
N1 - Copyright:
Copyright 2014 Elsevier B.V., All rights reserved.
PY - 2000
Y1 - 2000
N2 - We incorporate prior knowledge to construct nonlinear algorithms for invariant feature extraction and discrimination. Employing a unified framework in terms of a nonlinear variant of the Rayleigh coefficient' we propose non-linear generalizations of Fisher's discriminant and oriented PCA using Support Vector kernel functions. Extensive simulations show the utility of our approach.
AB - We incorporate prior knowledge to construct nonlinear algorithms for invariant feature extraction and discrimination. Employing a unified framework in terms of a nonlinear variant of the Rayleigh coefficient' we propose non-linear generalizations of Fisher's discriminant and oriented PCA using Support Vector kernel functions. Extensive simulations show the utility of our approach.
UR - http://www.scopus.com/inward/record.url?scp=84899018574&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84899018574&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84899018574
SN - 0262194503
SN - 9780262194501
T3 - Advances in Neural Information Processing Systems
SP - 526
EP - 532
BT - Advances in Neural Information Processing Systems 12 - Proceedings of the 1999 Conference, NIPS 1999
PB - Neural information processing systems foundation
T2 - 13th Annual Neural Information Processing Systems Conference, NIPS 1999
Y2 - 29 November 1999 through 4 December 1999
ER -