Unformatted text preview: Suggested Reading • Rifkin. Everything Old Is New Again: A Fresh Look at Historical Approaches in Machine Learning. MIT Ph.D. Thesis, 2002. < • Evgeniou, Pontil and Poggio. Regularization Networks and Support Vector Machines Advances in Computational Mathematics, 2000. • V. N. Vapnik. The Nature of Statistical Learning Theory. Springer, 1995....
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- Spring '04
- Machine Learning, Support Vector Machines, Vector Machines Advances, Ryan Rifkin, large SVMs