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  An Improved Training Algorithm for Kernel Fisher Discriminants

Mika, S., Schölkopf, B., & Smola, A. (2001). An Improved Training Algorithm for Kernel Fisher Discriminants. In T. Richardson, & T. Jaakkola (Eds.), 8th International Conference on Artificial Intelligence and Statistics (AISTATS 2001) (pp. 98-104). Society for Artificial Intelligence and Statistics.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-E30C-2 Version Permalink: https://hdl.handle.net/21.11116/0000-0005-A88C-0
Genre: Conference Paper

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http://www.gatsby.ucl.ac.uk/aistats/aistats2001/files/mika187.pdf (Any fulltext)
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 Creators:
Mika, S, Author
Schölkopf, B1, Author           
Smola, AJ1, Author           
Affiliations:
1External Organizations, ou_persistent22              

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 Abstract: We present a fast training algorithm for the kernel Fisher discriminant classifier. It uses a greedy approximation technique and has an empirical scaling behavior which improves upon the state of the art by more than an order of magnitude, thus rendering the kernel Fisher algorithm a viable option also for large datasets.

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 Dates: 2001-01
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: 2426
 Degree: -

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Title: 8th International Conference on Artificial Intelligence and Statistics (AISTATS 2001)
Place of Event: Key West, FL, USA
Start-/End Date: 2001-01-04 - 2001-01-07

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Title: 8th International Conference on Artificial Intelligence and Statistics (AISTATS 2001)
Source Genre: Proceedings
 Creator(s):
Richardson, TS, Editor
Jaakkola, TS, Editor
Affiliations:
-
Publ. Info: Society for Artificial Intelligence and Statistics
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 98 - 104 Identifier: -