该课程没有教科书。所有需要的信息将在每一堂课中以幻灯片的形式给出。在下面所列出的书籍和文章是有用的参考读物，特别是从理论的观点。额外的读物在 讲义 PDF文件中列出。
Cristianini, N., and J. Shawe-Taylor. Introduction To Support Vector Machines. Cambridge, 2000.
Cucker, F., and S. Smale. "On The Mathematical Foundations of Learning." Bulletin of the American Mathematical Society. 2002.
Devroye, L., L. Gyorfi, and G. Lugosi. A Probabilistic Theory of Pattern Recognition. Springer, 1997.
Evgeniou, T., M. Pontil, and T. Poggio. "Regularization Networks and Support Vector Machines." Advances in Computational Mathematics. 2000.
Poggio, T., and S. Smale. "The Mathematics of Learning: Dealing with Data." Notices of the AMS. 2003.
Vapnik, V. N. The Nature of Statistical Learning Theory. Springer, 1995.
———. Statistical Learning Theory. Wiley, 1998.