-
1
-
-
0032289099
-
Heteroscedastic discriminant analysis and reduced rank HMMS for improved speech recognition
-
N. Kumar and A.G. Andreou. Heteroscedastic discriminant analysis and reduced rank HMMS for improved speech recognition. Speech Communication, 26:283-297, 1998.
-
(1998)
Speech Communication
, vol.26
, pp. 283-297
-
-
Kumar, N.1
Andreou, A.G.2
-
3
-
-
3042673775
-
Linear dimensionality reduction via a heteroscedastic extension of LDA: The Chernoff criterion
-
June
-
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):32-739, June 2004.
-
(2004)
IEEE Transactions on Pattern Analysis and Machine Intelligence
, vol.26
, Issue.6
, pp. 32-739
-
-
Loog, M.1
Duin, R.P.W.2
-
7
-
-
0035393361
-
Multiclass linear dimension reduction by weighted pairwise Fisher criteria
-
July
-
M. Loog, R.P.W. Duin, and R. Haeb-Umbach. Multiclass linear dimension reduction by weighted pairwise Fisher criteria. IEEE Transactions on Puttern Analysis and Machine Intelligence, 23(7):762-766, July 2001.
-
(2001)
IEEE Transactions on Puttern Analysis and Machine Intelligence
, vol.23
, Issue.7
, pp. 762-766
-
-
Loog, M.1
Duin, R.P.W.2
Haeb-Umbach, R.3
-
8
-
-
10644221106
-
Uncorrelatecl heteroscedastic LDA based on the weighted pairwise Chernoff criterion
-
A.K. Qin, P.N. Suganthan, and M. Loog. Uncorrelatecl heteroscedastic LDA based on the weighted pairwise Chernoff criterion. Pattern Recognition, 2005.
-
(2005)
Pattern Recognition
-
-
Qin, A.K.1
Suganthan, P.N.2
Loog, M.3
-
10
-
-
0034300875
-
A new LDA-based face recognition system which can solve the small sample size problem
-
L.F. Chen, H.Y.M. Liao, M.T. Ko, J.C. Lin, and G.J. Yu. A new LDA-based face recognition system which can solve the small sample size problem. Pattern Recognition, 33:1713-1726, 2000.
-
(2000)
Pattern Recognition
, vol.33
, pp. 1713-1726
-
-
Chen, L.F.1
Liao, H.Y.M.2
Ko, M.T.3
Lin, J.C.4
Yu, G.J.5
-
11
-
-
0001765951
-
A direct LDA algorithm for high-dimensional data with application to face recognition
-
H. Yu and J. Yang. A direct LDA algorithm for high-dimensional data with application to face recognition. Pattern Recognition, 34:2067-2070, 2001.
-
(2001)
Pattern Recognition
, vol.34
, pp. 2067-2070
-
-
Yu, H.1
Yang, J.2
-
12
-
-
33751565280
-
Solving the small size problem of LDA
-
August
-
R. Huang, Q. Liu, H. Lu, and S. Ma. Solving the small size problem of LDA. In Proceedings of the Sixteenth International Conference on Pattern. Recognition, volume 3, pages 29-32, August 2002.
-
(2002)
Proceedings of the Sixteenth International Conference on Pattern. Recognition
, vol.3
, pp. 29-32
-
-
Huang, R.1
Liu, Q.2
Lu, H.3
Ma, S.4
-
13
-
-
0036487285
-
Why can LDA be performed in PCA transformed space?
-
J. Yang and J.Y. Yang. Why can LDA be performed in PCA transformed space? Pattern Recognition, 36:563-566, 2003.
-
(2003)
Pattern Recognition
, vol.36
, pp. 563-566
-
-
Yang, J.1
Yang, J.Y.2
-
14
-
-
13344287015
-
Discriminative common vectors for face recognition
-
H. Cevikalp, M. Neamtu, M. Wilkes, and A. Barkana. Discriminative common vectors for face recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence, 27(1):4-13, 2005.
-
(2005)
IEEE Transactions on Pattern Analysis and Machine Intelligence
, vol.27
, Issue.1
, pp. 4-13
-
-
Cevikalp, H.1
Neamtu, M.2
Wilkes, M.3
Barkana, A.4
-
15
-
-
0347243182
-
Nonlinear component analysis as a kernel eigenvalue problem
-
B. Schölkopf, A. Smola, and K.R. Müller. Nonlinear component analysis as a kernel eigenvalue problem. Neural Computation, 10:1299-1319, 1999.
-
(1999)
Neural Computation
, vol.10
, pp. 1299-1319
-
-
Schölkopf, B.1
Smola, A.2
Müller, K.R.3
-
16
-
-
0033337021
-
Fisher discriminant analysis with kernels
-
Y.H. Hu, J. Larsen, E. Wilson, and S. Douglas, editors
-
S. Mika, G. Rätsch, J. Weston, B. Schölkopf, and K.R. Müller. Fisher discriminant analysis with kernels. In Y.H. Hu, J. Larsen, E. Wilson, and S. Douglas, editors, Proceedings of the Neural Networks for Signal Processing IX, pages 41-48, 1999.
-
(1999)
Proceedings of the Neural Networks for Signal Processing IX
, pp. 41-48
-
-
Mika, S.1
Rätsch, G.2
Weston, J.3
Schölkopf, B.4
Müller, K.R.5
-
17
-
-
0034296402
-
Generalized discriminant analysis using a kernel approach
-
G. Baudat and F. Anouar. Generalized discriminant analysis using a kernel approach. Neural Computation, 12:2385-2404, 2000.
-
(2000)
Neural Computation
, vol.12
, pp. 2385-2404
-
-
Baudat, G.1
Anouar, F.2
-
18
-
-
84899008974
-
Efficient kernel discriminant analysis via QR decomposition
-
T. Xiong, J.P. Ye, Q. Li, V. Cherkassky, and R. Janardan. Efficient kernel discriminant analysis via QR decomposition. In Advances in Neural Information Processing Systems 17, 2005.
-
(2005)
Advances in Neural Information Processing Systems
, vol.17
-
-
Xiong, T.1
Ye, J.P.2
Li, Q.3
Cherkassky, V.4
Janardan, R.5
-
19
-
-
33144465195
-
Nonlinear discriminant analysis using kernel functions and the generalized singular value decomposition
-
to appear
-
C.H. Park and H. Park. Nonlinear discriminant analysis using kernel functions and the generalized singular value decomposition. SIAM Journal on Matrix Analysis and Application, to appear (http://www-users.cs.umn.edu/hpark/pub.html).
-
SIAM Journal on Matrix Analysis and Application
-
-
Park, C.H.1
Park, H.2
-
24
-
-
14544297033
-
KPCA plus LDA: A complete kernel Fisher discriminant framework for feature extraction and recognition
-
J. Yang, A.F. Frangi, J.Y. Yang, D. Zhang, and Z. Jin. KPCA plus LDA: a complete kernel Fisher discriminant framework for feature extraction and recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence, 27(2):230-244, 2005.
-
(2005)
IEEE Transactions on Pattern Analysis and Machine Intelligence
, vol.27
, Issue.2
, pp. 230-244
-
-
Yang, J.1
Frangi, A.F.2
Yang, J.Y.3
Zhang, D.4
Jin, Z.5
|