Call for NIPS 2008 Kernel Learning Workshop Submissions
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K.-R. M\"uller, A. Smola, G. R\"atsch, B. Sch\"ol\-kopf, J. Kohlmorgen, and V. Vapnik (1999)
Predicting Time Series with Support Vector Machines
In: Advances in Kernel Methods — Support Vector Learning, ed. by B. Schölkopf and C. J. C. Burges and A. J. Smola, pp. 243–254, Cambridge, MA, MIT Press.
SV regression with epsilon-insensitive and Huber loss functions. Experimental results on time-series prediction (Mackey-Glass and Santa Fe competition data set D, with a new record on the latter).
Short version appeared in ICANN'97, Springer Lecture Notes in Computer Science