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  Using support vector machines for time series prediction

Müller, K.-R., Smola, A., Rätsch, G., Schölkopf, B., Kohlmorgen, J., & Vapnik, V. (1999). Using support vector machines for time series prediction. In B. Schölkopf, C. Burges, & A. Smola (Eds.), Advances in kernel methods: support vector learning (pp. 243-253). Cambridge, MA, USA: MIT Press.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0005-C49B-F Version Permalink: http://hdl.handle.net/21.11116/0000-0005-C49C-E
Genre: Conference Paper

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Locator:
https://dl.acm.org/doi/10.5555/299094.299107 (Publisher version)
Description:
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 Creators:
Müller, K-R, Author              
Smola, AJ, Author              
Rätsch, G1, Author              
Schölkopf, B2, 3, Author              
Kohlmorgen, J, Author
Vapnik, V, Author              
Affiliations:
1Friedrich Miescher Laboratory, Max Planck Society, ou_2575692              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              
3Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497797              

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 Dates: 1999-02
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.5555/299094.299107
 Degree: -

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Title: Eleventh Annual Conference on Neural Information Processing (NIPS 1997)
Place of Event: Breckenridge, CO, USA
Start-/End Date: 1997-12-01 - 1997-12-06

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Title: Advances in kernel methods: support vector learning
Source Genre: Proceedings
 Creator(s):
Schölkopf, B1, Editor            
Burges, CJC, Editor
Smola, AJ, Editor            
Affiliations:
1 Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794            
Publ. Info: Cambridge, MA, USA : MIT Press
Pages: 376 Volume / Issue: - Sequence Number: - Start / End Page: 243 - 253 Identifier: ISBN: 978-0-262-19416-7