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Iterative Single Data Algorithm for Training Kernel Machines from Huge Data Sets: Theory and Performance

Kecman, Voijslav and Huang, Te-Ming and Vogt, Michael
Wang, Lipo (ed.) (2005):
Iterative Single Data Algorithm for Training Kernel Machines from Huge Data Sets: Theory and Performance.
In: Support Vector Machines : Theory and Applications, Berlin [u.a.], Springer, pp. 255-274, [Online-Edition: http://dx.doi.org/10.1007/10984697_12],
[Book Section]

Item Type: Book Section
Erschienen: 2005
Editors: Wang, Lipo
Creators: Kecman, Voijslav and Huang, Te-Ming and Vogt, Michael
Title: Iterative Single Data Algorithm for Training Kernel Machines from Huge Data Sets: Theory and Performance
Language: English
Title of Book: Support Vector Machines : Theory and Applications
Series Name: Studies in Fuzziness and Soft Computing
Volume: 2005
Number: 177
Place of Publication: Berlin [u.a.]
Publisher: Springer
ISBN: 3-540-24388-7
Divisions: 18 Department of Electrical Engineering and Information Technology
18 Department of Electrical Engineering and Information Technology > Institut für Automatisierungstechnik und Mechatronik
18 Department of Electrical Engineering and Information Technology > Institut für Automatisierungstechnik und Mechatronik > Regelungstechnik und Prozessautomatisierung
Date Deposited: 20 Nov 2008 08:23
Official URL: http://dx.doi.org/10.1007/10984697_12
Identification Number: doi:10.1007/10984697_12
License: [undefiniert]
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