1. Chang, C.-C., Lin, C.-J.: LIBSVM: a library for support vector machines. ACM Trans. Intell. Syst. Technol. 2 (2011).
https://www.csie.ntu.edu.tw/~cjlin/libsvm/
2. Duarte, M., Hu, Y.H.: Vehicle classification in distributed sensor networks. J. Parallel Distrib. Comput. 64, 826–838 (2004)
3. Ferrer, R., Planas, J., Bellens, P., Duran, A., González, M., Martorell, X., Badia, R.M., Ayguadé, E.,Labarta, J.: Optimizing the exploitation of multicore processors and GPUs with OpenMP and OpenCL. In: Vidal, R., Heyden, A., Ma, Y. (eds.) WDV 2006, WDV 2005. LNCS, vol. 6548, pp. 215–229. Springer, Heidelberg (2010)
4. Forina, M., et al.: PARVUS - An Extendible Package for Data Exploration, Classification and Correlation. Institute of Pharmaceutical and Food Analysis and Technologies, Via Brigata Salerno, 16147 Genoa, Italy. Stefan Aeberhard, Donor. email: stefancoral.cs.jcu.edu.au,
http://archive.ics.uci.edu/ml/datasets/Wine
5. Glasmachers, T., Igel, C.: Maximum-gain working set selection for SVMs. In: Bennett, K.P., Parrado-Hernández, E. (eds.) Journal of Machine Learning Research, vol. 7, pp. 1437–1466 (2006)