Asymptotic theory for regularization: One-dimensional linear case

Advances in Neural Information Processing Systems

Volumn , Issue , 1998, Pages 294-300

  Koistinen, Petri ^a  

^a UNIVERSITY OF HELSINKI   (Finland)

Author keywords

[No Author keywords available]

Indexed keywords

ASYMPTOTIC THEORIES; GENERALIZATION ABILITY; OPTIMAL REGULARIZATION; RIDGE REGRESSION; WEIGHT VECTOR;

REGRESSION ANALYSIS;

EID: 0344964709     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (8)

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2. Bishop, C. M. (1995). Neural Networks for Pattern Recognition. Oxford University Press.
3. Brockwell, P. J. and Davis, R. A. (1987). Time Series: Theory and Methods. Springer series in statistics. Springer-Verlag.
4. Hoerl, A. E. and Kennard, R. W. (1988). Ridge regression. In Kotz, S., Johnson, N. L., and Read, C. B., editors, Encyclopedia of Statistical Sciences. John Wiley & Sons, Inc.
5. Larsen, J. and Hansen, L. K. (1994). Generalization performance of regularized neural network models. In Vlontos, J., Whang, J.-N., and Wilson, E., editors, Proc. of the 4th IEEE Workshop on Neural Networks for Signal Processing, pages 42-51. IEEE Press.
6. Ripley, B. D. (1996). Pattern Recognition and Neural Networks. Cambridge University Press.
7. Serfling, R. J. (1980). Approximation Theorems of Mathematical Statistics. John Wiley & Sons, Inc.
8. Titterington, D. M. (1985). Common structure of smoothing techniques in statistics. International Statistical Review, 53:141-170.