Nonlinear discriminant analysis uhing kernel function

Advances in Neural Information Processing Systems

Volumn , Issue , 2000, Pages 568-574

  Roth, Volker ^a   Steinhage, Volker ^a  

^a UNIVERSITY OF BONN   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; FACE RECOGNITION; SELF ORGANIZING MAPS; VECTORS;

LINEAR DECISION BOUNDARY; LINEAR DISCRIMINANT ANALYSIS; LOW-DIMENSIONAL SUBSPACE; MULTIVARIATE TECHNIQUES; NONLINEAR DISCRIMINANT ANALYSIS; NONLINEAR GENERALIZATIONS; PROTOTYPE CLASSIFIERS; SEMI-SUPERVISED DISCRIMINANT ANALYSIS;

DISCRIMINANT ANALYSIS;

EID: 84898984897     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (14)

1. R. Duda and P. Hart, Pattern Classification and Scene Analysis. Wiley & Sons, 1973.
2. T. Hastie, R. Tibshirani, and A. Buja, "Flexible discriminant analysis by optimal scoring," JASA, vol. 89, pp. 1255-1270, 1994.
3. V. N. Vapnik, Statistical learning theory. Wiley & Sons, 1998.
4. B. Scholkopf, A. Smola, and K.-R. Muller, "Nonlinear component analysis as a kernel eigenvalue problem," Neural Computation, vol. 10, no. 5, pp. 1299-1319, 1998.
5. S. Mika, G. Ratsch, J. Weston, B. Scholkopf, and K.-R. Muller, "Fisher discriminant analysis with kernels," in Neural Networks for Signal Processing IX (Y.-H. Hu, J. Larsen, E. Wilson, and S. Douglas, eds.), pp. 41-48, IEEE, 1999.
6. V. Roth and V. Steinhage, "Nonlinear discriminant analysis using kernel functions," Tech. Rep. IAI-TR-99-7, Department of Computer Science III, Bonn University, 1999.
7. V. Roth, A. Pogoda, V. Steinhage, and S. Schroder, "Pattern recognition combining feature- and pixel-based classification within a real world application," in Muster-erkennung 1999 (W. Forstner, J. Buhmann, A. Faber, and P. Faber, eds.), Informatik aktuell, pp. 120-129, 21. DAGM Symposium, Bonn, Springer, 1999.
8. T. Hastie, A. Buja, and R. Tibshirani, "Penalized discriminant analysis," AnnStat, vol. 23, pp. 73-102, 1995.
9. S. Saunders, A. Gammermann, and V. Vovk, "Ridge regression learning algorithm in dual variables," tech. rep., Royal Holloway, University of London, 1998.
10. L. Breiman, J. H. Friedman, R. A. Olshen, and C. J. Stone, Classification and Regression Trees. Monterey, CA: Wadsworth and Brooks/Cole, 1984.
11. T. Hastie and R. Tibshirani, "Discriminant analysis by gaussian mixtures," JRSSB, vol. 58, pp. 158-176, 1996.
12. B. Scholkopf, Support Vector Learning. PhD thesis, 1997. R. Oldenbourg Verlag, Munich.
13. T. Joachims, "Making large-scale svm learning practical," in Advances in Kernel Methods - Support Vector Learning (B. Scholkopf, C. Burges, and A. Smola, eds.), MIT Press, 1999.
14. B. Flury, A First Course in Multivariate Statistics. Springer, 1997.