Worst-case linear discriminant analysis

Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010, NIPS 2010

Volumn , Issue , 2010, Pages

  Zhang, Yu ^a   Yeung, Dit Yan ^a  

^a HONG KONG UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Hong Kong)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE;

AVERAGE-CASE; DATAPOINTS; DIMENSIONALITY REDUCTION; DIMENSIONALITY REDUCTION METHOD; DISCRIMINANT ANALYSIS MODEL; HIGH DIMENSIONALITY; LINEAR DISCRIMINANT ANALYZE; OPTIMIZATION PROBLEMS; TRAINING DATA; WITHIN CLASS SCATTER;

DISCRIMINANT ANALYSIS;

EID: 85162035389     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (24)

1. A. Asuncion and D.J. Newman. UCI machine learning repository, 2007.
2. P. N. Belhumeur, J. P. Hespanha, and D. J. Kriegman. Eigenfaces vs. Fisherfaces: Recognition using class specific linear projection. IEEE Transactions on Pattern Analysis and Machine Intelligence, 19(7):711-720, 1997.
3. S. Boyd and L. Vandenberghe. Convex Optimization. Cambridge University Press, New York, NY, 2004.
4. J. V. Davis, B. Kulis, P. Jain, S. Sra, and I. S. Dhillon. Information-theoretic metric learning. In Proceedings of the Twenty-Fourth International Conference on Machine Learning, pages 209-216, Corvalis, Oregon, USA, 2007.
5. J. Duchene and S. Leclercq. An optimal transformation for discriminant and principal component analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence, 10(6):978-983, 1988.
6. D. H. Foley and J.W. Sammon. An optimal set of discriminant vectors. IEEE Transactions on Computers, 24(3):281-289, 1975.
7. K Fukunnaga. Introduction to Statistical Pattern Recognition. Academic Press, New York, 1991.
8. I. T. Jolliffe. Principal Component Analysis. Springer-Verlag, New York, 2nd edition, 2002.
9. S.-J. Kim, A. Magnani, and S. Boyd. Robust Fisher discriminant analysis. In Y. Weiss, B. Schölkopf, and J. Platt, editors, Advances in Neural Information Processing Systems 18, pages 659-666. Vancouver, British Columbia, Canada, 2006.
10. A. Kocsor, K. Kovács, and C. Szepesvári. Margin maximizing discriminant analysis. In Proceedings of the 15th European Conference on Machine Learning, pages 227-238, Pisa, Italy, 2004.
11. H. Li, T. Jiang, and K. Zhang. Efficient and robust feature extraction by maximum margin criterion. In S. Thrun, L. K. Saul, and B. Schölkopf, editors, Advances in Neural Information Processing Systems 16, Vancouver, British Columbia, Canada, 2003.
12. M. S. Lobo, L. Vandenberghe, S. Boyd, and H. Lebret. Applications of second-order cone programming. Linear Algebra and its Applications, 284:193-228, 1998.
13. A. M. Martínez and R. Benavente. The AR-face database. Technical Report 24, CVC, 1998.
14. S. Mika, G. Rätsch, J.Weston, B. Schölkopf, A. J. 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):623-633, 2003.
15. S. A. Nene, S. K. Nayar, and H. Murase. Columbia object image library (COIL-20). Technical Report 005, CUCS, 1996.
16. M. L. Overton and R. S. Womersley. Optimality conditions and duality theory for minimizing sums of the largest eigenvalues of symmetric matrices. Math Programming, 62(2):321-357, 1993.
17. T. Sim, S. Baker, and M. Bsat. The CMU pose, illumination and expression database. IEEE Transactions on Pattern Analysis and Machine Intelligence, 25(12):1615-1618, 2003.
18. A. J. Smola, S. V. N. Vishwanathan, and T. Hofmann. Kernel methods for missing variables. In Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, Barbados, 2005.
19. L. Vandenberghe and S. Boyd. Semidefinite prgramming. SIAM Review, 38(1):49-95, 1996.
20. H. Wang, S. Yan, D. Xu, X. Tang, and T. Huang. Trace ratio vs. ratio trace for dimensionality reduction. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pages 1-8, Minneapolis, Minnesota, USA, 2007.
21. K. Q. Weinberger, J. Blitzer, and L. K. Saul. Distance metric learning for large margin nearest neighbor classification. In Y.Weiss, B. Schölkopf, and J. Platt, editors, Advances in Neural Information Processing Systems 18, pages 1473-1480, Vancouver, British Columbia, Canada, 2005.
22. E. P. Xing, A. Y. Ng, M. I. Jordan, and S. J. Russell. Distance metric learning with application to clustering with side-information. In S. Becker, S. Thrun, and K. Obermayer, editors, Advances in Neural Information Processing Systems 15, pages 505-512, Vancouver, British Columbia, Canada, 2002.
23. J.-P. Ye and T. Xiong. Computational and theoretical analysis of null space and orthogonal linear discriminant analysis. Journal of Machine Learning Research, 7:1183-1204, 2006.
24. A. Yuille and A. Rangarajan. The concave-convex procedure. Neural Computation, 15(4):915-936, 2003.