Zheng W. (2006). Class-incremental generalized discriminant analysis. Neural computation. 18 [PubMed]

See more from authors: Zheng W

References and models cited by this paper

Baudat G, Anouar F. (2000). Generalized discriminant analysis using a kernel approach. Neural computation. 12 [PubMed]

Belhumeur PN, Hespanha JP, Kriegman DJ. (1997). Eigenfaces vs. Fisherfaces: recognition using class specific linear projection IEEE Transactions On Pattern Analysis And Machine Intelligen. 19

Bjorck A. (1967). Solving linear least squares problems using Gram-Schmidt orthogonalization BIT. 7

Bjorck A. (1994). Numerics of Gram-Schmidt orthogonalization Linear Algebra and Its Applications. 197

Cevikalp H, Neamtu M, Wilkes M, Barkana A. (2005). Discriminative common vectors for face recognition. IEEE transactions on pattern analysis and machine intelligence. 27 [PubMed]

Cevikalp H, Wilkes M. (2004). Face recognition by using discriminant common vectors Proceedings Of The 17th International Conference On Pattern Recognition.

Duda RO, Hart PE. (1973). Pattern Classification and Scene Analysis.

Fukunaga K. (1990). Introduction to statistical pattern recognition (2nd ed).

Li Q, Cherkassky V, Xiong T, Ye J, Janardan R. (2005). Efficient kernel discriminant analysis via QR decomposition Advances in neural information processing systems. 17

Li Q et al. (2004). IDR-QR: An incremental dimension reduction algorithm via QR decomposition Proceedings of the 2004 ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.

Lin JC, Chen LF, Liao HYM, Ko MT, Yu GJ. (2000). A new LDA-based face recognition system which can solve the small sample size problem Pattern Recognition. 33

Lu J, Plataniotis KN, Venetsanopoulos AN. (2003). Face recognition using kernel direct discriminant analysis algorithms. IEEE transactions on neural networks. 14 [PubMed]

Martinez AM, Benavente R. (1998). The AR face database CVC Tech Rep No 24.

Pentland A, Turk M. (1991). Eigen faces for recognition J Cogn Neurosci. 3

Rice JR. (1966). Experiments on Gram-Schmidt orthogonalization Mathematics Computation. 20

Scholkopf B, Smola A, Muller KR. (1998). Nonlinear component analysis as a kernel eigenvalue problem Neural Comput. 10

Vapnik V. (1995). The Nature of Statistical Learning Theory.

Wang Y, Liu W, Li SZ, Tan T. (2004). Null space-based kernel Fisher discriminant analysis for face recognition Proceedings of the Sixth International conference on Automatic Face and Gesture Recognition.

Wolf L, Shashua A. (2003). Learning over sets using kernel principal angles J Mach Learn Res. 4

Yang J, Frangi AF, Jin Z, Yang JY. (2004). Essence of kernel Fisher discriminant: KPCA plus LDA Pattern Recognition. 37

Zhao L, Zheng W, Zou C. (2004). An efficient algorithm to solve the small sample size problem for LDA Pattern Recognition. 37

Zhao L, Zheng W, Zou C. (2004). Real-time face recognition using Gram-Schmidt orthogonalization algorithm for LDA Proceedings of the 17th International Conference on Pattern Recognition.

Zheng W, Zhao L, Zou C. (2004). A modified algorithm for generalized discriminant analysis. Neural computation. 16 [PubMed]

Zheng W, Zhao L, Zou C. (2005). Foley-Sammon optimal discriminant vectors using kernel approach. IEEE transactions on neural networks. 16 [PubMed]

References and models that cite this paper
This website requires cookies and limited processing of your personal data in order to function. By continuing to browse or otherwise use this site, you are agreeing to this use. See our Privacy policy and how to cite and terms of use.