Local discriminant analysis

Proceedings - International Conference on Pattern Recognition

Volumn 3, Issue , 2006, Pages 328-331

  Loog, Marco ^a   De Ridder, Dick ^b  

^a IT UNIVERSITY OF COPENHAGEN   (Denmark)

^b DELFT UNIVERSITY OF TECHNOLOGY   (Netherlands)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL METHODS; CONFORMAL MAPPING; FISHER INFORMATION MATRIX; PROBLEM SOLVING;

LOCAL DISCRIMINANT ANALYSIS (LDA); NONLINEAR DIMENSIONALITY REDUCTION TECHNIQUE; NONLINEAR REDUCTION METHODS;

LINEAR PROGRAMMING;

EID: 34147095907     PISSN: 10514651     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICPR.2006.769     Document Type: Conference Paper

References (18)

1. M. Belkin and P. Niyogi. Laplacian eigenmaps for dimensionality reduction and data representation. Neural Computation, 15(6):1373-1396, 2003.
2. H. Brunzell and J. Eriksson. Feature reduction for classification of multidimensional data. Pattern Recognition, 33:1741-1748, 2000.
3. E. Choi and C. Lee. Feature extraction based on the Bhattacharyya distance. Pattern Recognition, 36:1703-1709, 2003.
4. D. de Ridder, O. Kouropteva, O. Okun, M. Pietikäinen, and R. P. W. Duin. Supervised locally linear embedding. In Proceedings of the ICANN 2003, volume 2714 of Lecture Notes in Computer Science, pages 333-341, 2003.
5. P. A. Devijver and J. Kittler. Pattern recognition: a statistical approach. Prentice-Hall, 1982.
6. R. O. Duda and P. B. Hart. Pattern classification and scene analysis. John Wiley & Sons, 1973.
7. T. Hastie, A. Buja, and R. Tibshirani. Penalized discriminant analysis. Annals of statistics, 23:73-102, 1995.
8. T. Hastie, R. Tibshirani, and A. Buja. Flexible discriminant analysis by optimal scoring. Journal of the American Statistical Association, 89(428):1255-1270, 1994.
9. T. Hastie, R. Tibshirani, and J. Friedman. The Elements of Statistical Learning. Springer Series in Statistics. Springer-Verlag, New York . Berlin . Heidelberg, 2001.
10. S.D. Kamvar, D. Klein, and C.D. Manning. Spectral learning. In Proceedings of the IJCAI 2003, 2003.
11. O. Kouropteva, O. Okun, and M. Pietikäinen. Supervised locally linear embedding algorithm for pattern recognition. In Proceedings of the IbPRIA 2003, volume 2652 of Lecture Notes in Computer Science, pages 386-394, 2003.
12. M. Loog and R. P. W. Duin. Linear dimensionality reduction via a heteroscedastic extension of LDA: The Chernoff criterion. IEEE Transactions on Pattern Analysis and Machine Intelligence, 26(6):732739, 2004.
13. S. Mika, G. Ratsch, J. Weston, B. Schölkopf, A. Smola, and K.-R. Müller. Constructing descriptive and discriminative nonlinear features: Rayleigh coefficients in kernel feature spaces. IEEE Transactions on Pattern Analysis and Machine Intelligence, 25(5):623-628, 2003.
14. D. de Ridder, M. Loog, and M.J.T. Reinders. Local Fisher embedding. In Proceedings of the 17th International Conference on Pattern Recognition, pages 295-298, 2004.
15. S. T. Roweis and L. K. Saul. Nonlinear dimensionality reduction by locally linear embedding. Science, 290(5500):2323-2326, 2000.
16. B. Schölkopf, A. Smola, and K.-R. Müller. Nonlinear component analysis as a kernel eigenvalue problem. Neural Computation, 10(5):1299-1319, 1998.
17. J. B. Tenenbaum, V. de Silva, and J. C. Langford. A global geometric framework for nonlinear dimensionality reduction. Science, 290(5500):2319-2323, 2000.
18. M.-H. Yang. Extended isomap for classification. In Proceedings of the 16th International Conference on Pattern Recognition, pages 615-618, 2002.