TY - GEN
T1 - Online learning with kernels
AU - Kivinen, Jyrki
AU - Smola, Alex J.
AU - Williamson, Robert C.
PY - 2002
Y1 - 2002
N2 - We consider online learning in a Reproducing Kernel Hilbert Space. Our method is computationally efficient and leads to simple algorithms. In particular we derive update equations for classification, regression, and novelty detection. The inclusion of the ε -trick allows us to give a robust parameterization. Moreover, unlike in batch learning where the ε -trick only applies to the ν -insensitive loss function we are able to derive general trimmed-mean types of estimators such as for Huber's robust loss.
AB - We consider online learning in a Reproducing Kernel Hilbert Space. Our method is computationally efficient and leads to simple algorithms. In particular we derive update equations for classification, regression, and novelty detection. The inclusion of the ε -trick allows us to give a robust parameterization. Moreover, unlike in batch learning where the ε -trick only applies to the ν -insensitive loss function we are able to derive general trimmed-mean types of estimators such as for Huber's robust loss.
UR - http://www.scopus.com/inward/record.url?scp=84898940321&partnerID=8YFLogxK
M3 - Conference contribution
SN - 0262042088
SN - 9780262042086
T3 - Advances in Neural Information Processing Systems
BT - Advances in Neural Information Processing Systems 14 - Proceedings of the 2001 Conference, NIPS 2001
PB - Neural Information Processing Systems Foundation
T2 - 15th Annual Neural Information Processing Systems Conference, NIPS 2001
Y2 - 3 December 2001 through 8 December 2001
ER -