Generalization performance of some learning problems in hilbert functional spaces

Advances in Neural Information Processing Systems

Volumn , Issue , 2002, Pages

  Zhang, Tong ^a  

^a IBM T J WATSON RESEARCH CENTER   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

FUNCTIONAL SPACES; GENERALIZATION BOUND; GENERALIZATION PERFORMANCE; HILBERT; LEARNING FORMULATION; LEARNING PROBLEM;

EID: 0042276471     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (7)

1. Olivier Bousquet and Andre Elisseeff. Algorithmic stability and generalization performance. In Todd K. Leen, Thomas G. Dietterich, and Volker Tresp, editors, Advances in Neural Information Processing Systems 13, pages 196-202. MIT Press, 2001.
2. Nello Cristianini and John Shawe-Taylor. An Introduction to Support Vector Machines and other Kernel-based Learning Methods. Cambridge University Press, 2000.
3. Wee Sun Lee, Peter L. Bartlett, and Robert C. Williamson. The importance of convexity in learning with squared loss. IEEE Trans. Inform. Theory, 44(5):1974-1980, 1998.
4. R. Tyrrell Rockafellar. Convex analysis. Princeton University Press, Princeton, NJ, 1970.
5. Vadim Yurinsky. Sums and Gaussian vectors. Springer-Verlag, Berlin, 1995.
6. Tong Zhang. Convergence of large margin separable linear classification. In Advances in Neural Information Processing Systems 13, pages 357-363, 2001.
7. Tong Zhang. A leave-one-out cross validation bound for kernel methods with applications in learning. In 14th Annual Conference on Computational Learning Theory, pages 427-443, 2001.