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- Kazushi Ikeda, Takemasa Yamasaki
- Neurocomputing
- 2007

- Takemasa Yamasaki, Kazushi Ikeda, Yoshihiko Nomura
- 2007 IEEE Symposium on Foundations of…
- 2007

Support vector machines (SVMs) are known to result in a quadratic programming problem, that requires a large computational complexity. To overcome this problem, the authors proposed two incremental SVMs from geometrical point of view in the previous study, both have a linear complexity with respect to the number of examples on average. One method was shown… (More)

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