Hi Spyros Skouras,
there is at least this paper:
K.-R. Müller, A. Smola, G. Rätsch, B. Schölkopf, J. Kohlmorgen, and
V. Vapnik. Using support vector machines for time series prediction. In
B. Schölkopf, C. Burges, and A. Smola, editors, Advances in Kernel
Methods
- Support Vector Learning, Proc. of the NIPS Workshop on Support
Vectors.
MIT Press, Cambridge, MA, 1998.
http://ida.first.gmd.de/~raetsch/ps/MueSmoRaeSchKohVap98_final.ps.gz
Somewhat related is this paper:
G. Rätsch, A. Demiriz, and K. Bennett. Sparse regression ensembles in
infinite and finite hypothesis spaces. NeuroCOLT2 technical report,
Royal
Holloway College, London, September 2000.
http://ida.first.gmd.de/~raetsch/ps/RaeDemBen00.ps.gz
both papers are contain some empirical evaluation of SVM or SVM like
methods.
Also have a look to http://www.kernel-machines.org
Hope that helps,
Gunnar
Spyros Skouras wrote:
>
> Dear community,
>
> I am new to SVMs and would like to know if there has ben any research on
> using SVMs for forecasting time series. I am looking for both theoretical
> results and any good applied papers.
>
> On a different note I would also like to know if anyone has considered the
> relationship between rationality and learning using SVMs.
>
> Thanks,
> Spyros Skouras
--
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Gunnar R"atsch, GMD First Berlin
Tel : +49 30 6392 1906
WWW : http://www.first.gmd.de/~raetsch
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