-
2
-
-
0043278893
-
Laplacian eigenmaps and sepctral techniques for embedding and clustering
-
M. Belkin and P. Niyogi. Laplacian eigenmaps and sepctral techniques for embedding and clustering. In Advances in Neural Information Processing Systems, volume 15, 2001. 1, 3
-
(2001)
Advances in Neural Information Processing Systems
, vol.15
, Issue.1
, pp. 3
-
-
Belkin, M.1
Niyogi, P.2
-
3
-
-
33750729556
-
Manifold regularization: A geometric framework for learning from examples
-
7
-
M. Belkin, P. Niyogi, and V. Sindhwani. Manifold regularization: a geometric framework for learning from examples. Journal of Machine Learning Research, 7:2399-2434, 2006. 1, 6
-
(2006)
Journal of Machine Learning Research
, vol.2399-2434
, Issue.1
, pp. 6
-
-
Belkin, M.1
Niyogi, P.2
Sindhwani, V.3
-
4
-
-
33749252873
-
-
The MIT Press, Cambridge, MA
-
O. Chapelle, B. Schölkopf, and A. Zien. Semi-Supervised Learning. The MIT Press, Cambridge, MA, 2006. 6
-
(2006)
Semi-Supervised Learning
, pp. 6
-
-
Chapelle, O.1
Schölkopf, B.2
Zien, A.3
-
5
-
-
0003882879
-
-
American Mathematical Society
-
F. R. Chung. Spectral Graph Theory. American Mathematical Society, 1997. 1
-
(1997)
Spectral Graph Theory
, pp. 1
-
-
Chung, F.R.1
-
6
-
-
35148866030
-
-
V. de Silva and J. Tenenbaum. Global versus local methods in nonlinear dimensionality reduction. In Advances in Neural Information Processing Systems, pages 705-712, 2002. 1
-
V. de Silva and J. Tenenbaum. Global versus local methods in nonlinear dimensionality reduction. In Advances in Neural Information Processing Systems, pages 705-712, 2002. 1
-
-
-
-
8
-
-
0036489046
-
Comparison of discrimination methods for the classification of tumors using gene expression data
-
97457
-
S. Dudoit, J. Fridlyand, and T. P. Speed. Comparison of discrimination methods for the classification of tumors using gene expression data. Journal of the American Statistical Association, 97(457):77-87, 2002. 1
-
(2002)
Journal of the American Statistical Association
, vol.77-87
, pp. 1
-
-
Dudoit, S.1
Fridlyand, J.2
Speed, T.P.3
-
9
-
-
0000764772
-
The use of multiple measurements in taxonomic problems
-
R. Fisher. The use of multiple measurements in taxonomic problems. Annals of Eugenics, 7:179-188, 1936. 1
-
(1936)
Annals of Eugenics
, vol.7
, Issue.179-188
, pp. 1
-
-
Fisher, R.1
-
10
-
-
33749128624
-
-
Academic Press, San Diego, California, USA
-
K. Fukunaga. Introduction to Statistical Pattern Classification. Academic Press, San Diego, California, USA, 1990. 1, 2
-
(1990)
Introduction to Statistical Pattern Classification
, vol.1
, pp. 2
-
-
Fukunaga, K.1
-
11
-
-
0004236492
-
-
The Johns Hopkins University Press, Baltimore, MD, USA, third edition
-
G. H. Golub and C. F. Van Loan. Matrix Computations. The Johns Hopkins University Press, Baltimore, MD, USA, third edition, 1996. 2, 3
-
(1996)
Matrix Computations
, vol.2
, pp. 3
-
-
Golub, G.H.1
Van Loan, C.F.2
-
12
-
-
0003684449
-
-
Springer
-
T. Hastie, R. Tibshirani, and J. Friedman. The Elements of Statistical Learning : Data mining, Inference, and Prediction. Springer, 2001. 1
-
(2001)
The Elements of Statistical Learning : Data mining, Inference, and Prediction
, pp. 1
-
-
Hastie, T.1
Tibshirani, R.2
Friedman, J.3
-
15
-
-
21844512674
-
Discriminant analysis with singular covariance matrices: Methods and applications to spectroscopic data
-
W. Krzanowski, P. Jonathan, W. McCarthy, and M. Thomas. Discriminant analysis with singular covariance matrices: methods and applications to spectroscopic data. Applied Statistics, 44:101-115, 1995. 1
-
(1995)
Applied Statistics
, vol.44
, Issue.101-115
, pp. 1
-
-
Krzanowski, W.1
Jonathan, P.2
McCarthy, W.3
Thomas, M.4
-
18
-
-
0003235939
-
Statistical learning theory
-
V. Vapnik. Statistical learning theory. Wiley, New York, 1998. 1
-
(1998)
Wiley, New York
, pp. 1
-
-
Vapnik, V.1
-
20
-
-
25144481906
-
Semi-supervised protein classification using cluster kernels
-
2115
-
W Weston, C. Leslie, E. Ie, D. Zhou, A. Elisseeff, and W. Noble. Semi-supervised protein classification using cluster kernels. Bioinformatics, 21(15):3241-3247, 2005. 6
-
(2005)
Bioinformatics
, vol.3241-3247
, pp. 6
-
-
Weston, W.1
Leslie, C.2
Ie, E.3
Zhou, D.4
Elisseeff, A.5
Noble, W.6
-
21
-
-
21844447839
-
-
J. Ye. Characterization of a family of algorithms for generalized discriminant analysis on undersampled problems. Journal of Machine Learning Research, 6:483-502, 2005. 1, 2, 4
-
J. Ye. Characterization of a family of algorithms for generalized discriminant analysis on undersampled problems. Journal of Machine Learning Research, 6:483-502, 2005. 1, 2, 4
-
-
-
-
23
-
-
33745743918
-
Computational and theoretical analysis of null space and orthogonal linear discriminant analysis
-
7
-
J. 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. 4
-
(2006)
Journal of Machine Learning Research
, vol.1183-1204
, pp. 4
-
-
Ye, J.1
Xiong, T.2
-
24
-
-
35148859643
-
-
D. Zhou, O. Bousquet, T. Lal, J. Weston, and B. Schölkopf. Learning with local and global consistency. In Advances in Neural Information Processing Systems, pages 321-328, 2003. 6
-
D. Zhou, O. Bousquet, T. Lal, J. Weston, and B. Schölkopf. Learning with local and global consistency. In Advances in Neural Information Processing Systems, pages 321-328, 2003. 6
-
-
-
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