Author:
Doi Koichiro,Yamashita Tetsuya,Yamamoto Akihiro
Publisher
Springer Berlin Heidelberg
Reference12 articles.
1. Cristianini, N., Shawe-Taylor, J.: An Introduction to Support Vector Machines and other kernel-based learning methods. Cambridge University Press, Cambridge (2000)
2. Gärtner, T.: A survey of kernel for structured data. SIGKDD Explorations 5(1), 268–275 (2003)
3. Gärtner, T., Lloyd, J.W., Flach, P.A.: Kernels and distances for structured data. Machine Learning 57(3), 205–232 (2004)
4. Haussler, D.: Convolution kernels on discrete structures. Technical report, University of California - Santa Cruz (1999)
5. Joachims, T.: Making large-scale support vector machine learning practical. In: Schölkopf, B., Burges, C., Smola, A. (eds.) Advances in Kernel Methods: Support Vector Machines, pp. 169–184. MIT Press, Cambridge (1998)
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