-
1
-
-
0042378381
-
Laplacian Eigenmaps for dimensionality reduction and data representation
-
Belkin, M., & Niyogi, P. (2003). Laplacian Eigenmaps for dimensionality reduction and data representation. Neural Computation, 15, 1373-1396.
-
(2003)
Neural Computation
, vol.15
, pp. 1373-1396
-
-
Belkin, M.1
Niyogi, P.2
-
2
-
-
33750729556
-
Manifold regularization: A geometric framework for learning from, labeled and unlabeled examples
-
Belkin, M., Niyogi, P., & Sindhwani, V. (2006). Manifold regularization: A geometric framework for learning from, labeled and unlabeled examples. Journal of Machine Learning Research, 7, 2399-2434.
-
(2006)
Journal of Machine Learning Research
, vol.7
, pp. 2399-2434
-
-
Belkin, M.1
Niyogi, P.2
Sindhwani, V.3
-
3
-
-
34547980564
-
Out-of-sample extensions for LLE, Isomap, MDS, Eigenmaps, and spectral clustering
-
1238, Département d'Informatique et Recherche Opérationnelle, Université de Montréal
-
Bengio, Y., Paiement, J.-F., & Vincent, P. (2003). Out-of-sample extensions for LLE, Isomap, MDS, Eigenmaps, and spectral clustering (Technical Report 1238). Département d'Informatique et Recherche Opérationnelle, Université de Montréal.
-
(2003)
Technical Report
-
-
Bengio, Y.1
Paiement, J.-F.2
Vincent, P.3
-
5
-
-
19644394100
-
Geometric diffusions as a tool for harmonic analysis and structure definition of data: Diffusion maps
-
Coifman, R., Lafon, S., Lee, A., Maggioni, M., Nadler, B., Warner, F., & Zucker, S. (2005). Geometric diffusions as a tool for harmonic analysis and structure definition of data: Diffusion maps. Proceedings of the National Academy of Sciences USA, 102, 7426-7431.
-
(2005)
Proceedings of the National Academy of Sciences USA
, vol.102
, pp. 7426-7431
-
-
Coifman, R.1
Lafon, S.2
Lee, A.3
Maggioni, M.4
Nadler, B.5
Warner, F.6
Zucker, S.7
-
8
-
-
0012657603
-
Dimension reduction and visualization in discriminant analysis (with discussion)
-
Cook, R. D., & Yin, X. (2001). Dimension reduction and visualization in discriminant analysis (with discussion). Australian & New Zealand Journal of Statistics, 43, 147-199.
-
(2001)
Australian & New Zealand Journal of Statistics
, vol.43
, pp. 147-199
-
-
Cook, R.D.1
Yin, X.2
-
9
-
-
0037948870
-
Hessian eigenmaps: Locally linear embedding techniques for high-dimensional data
-
Donoho, D. L., & Grimes, C. (2003). Hessian eigenmaps: Locally linear embedding techniques for high-dimensional data. Proceedings of the National Academy of Sciences USA, 100, 5591-5596.
-
(2003)
Proceedings of the National Academy of Sciences USA
, vol.100
, pp. 5591-5596
-
-
Donoho, D.L.1
Grimes, C.2
-
10
-
-
4544371135
-
Dimensionality reduction for supervised learning with reproducing kernel Hilbert spaces
-
Fukumizu, K., Bach, F. R., & Jordan, M. I. (2004). Dimensionality reduction for supervised learning with reproducing kernel Hilbert spaces. Journal of Machine Learning Research, 5, 73-99.
-
(2004)
Journal of Machine Learning Research
, vol.5
, pp. 73-99
-
-
Fukumizu, K.1
Bach, F.R.2
Jordan, M.I.3
-
11
-
-
34547965764
-
Kernel dimension reduction in regression
-
Department of Statistics, University of California, Berkeley
-
Fukumizu, K., Bach, F. R., & Jordan, M. I. (2006). Kernel dimension reduction in regression (Technical Report). Department of Statistics, University of California, Berkeley.
-
(2006)
Technical Report
-
-
Fukumizu, K.1
Bach, F.R.2
Jordan, M.I.3
-
13
-
-
11144299132
-
A kernel view of the dimensionality reduction of manifolds
-
ACM
-
Ham, J., Lee, D., Mika, S., & Scholkopf, B. (2004). A kernel view of the dimensionality reduction of manifolds. Proceedings of the 21 'st International Conference on Machine Learning. ACM.
-
(2004)
Proceedings of the 21 'st International Conference on Machine Learning
-
-
Ham, J.1
Lee, D.2
Mika, S.3
Scholkopf, B.4
-
15
-
-
26444566340
-
Contour regression: A general approach to dimension reduction
-
Li, B., Zha, H., & Chiaramonte, F. (2005). Contour regression: A general approach to dimension reduction. The Annals of Statistics, 33, 1580-1616.
-
(2005)
The Annals of Statistics
, vol.33
, pp. 1580-1616
-
-
Li, B.1
Zha, H.2
Chiaramonte, F.3
-
17
-
-
0001659464
-
On principal Hessian directions for data visualization and dimension reduction: Another application of Stein's lemma
-
Li, K.-C. (1992). On principal Hessian directions for data visualization and dimension reduction: Another application of Stein's lemma. Journal of the American Statistical Association, 86, 316-342.
-
(1992)
Journal of the American Statistical Association
, vol.86
, pp. 316-342
-
-
Li, K.-C.1
-
18
-
-
34547978155
-
-
Remote Sensing Systems (2004). Microwave sounding units (MSU) data, sponsored by the NOAA Climate and Global Change Program. Data available at www.remss.com.
-
Remote Sensing Systems (2004). Microwave sounding units (MSU) data, sponsored by the NOAA Climate and Global Change Program. Data available at www.remss.com.
-
-
-
-
19
-
-
0034704222
-
Nonlinear dimensionality reduction by locally linear embedding
-
Roweis, S., & Saul, L. (2000). Nonlinear dimensionality reduction by locally linear embedding. Science, 290, 2323-2326.
-
(2000)
Science
, vol.290
, pp. 2323-2326
-
-
Roweis, S.1
Saul, L.2
-
22
-
-
0034704229
-
A global geometric framework for nonlinear dimensionality reduction
-
Tenenbaum, J., de Silva, V., & Langford, J. (2000). A global geometric framework for nonlinear dimensionality reduction. Science, 290, 2319-2322.
-
(2000)
Science
, vol.290
, pp. 2319-2322
-
-
Tenenbaum, J.1
de Silva, V.2
Langford, J.3
-
23
-
-
33749248511
-
Semi-supervised nonlinear dimensionality reduction
-
ACM
-
Yang, X., Fu, H., Zha, H., & Barlow, J. (2006). Semi-supervised nonlinear dimensionality reduction. Proceedings of the 23 'rd International Conference on Machine Learning (pp. 1065-1072). ACM.
-
(2006)
Proceedings of the 23 'rd International Conference on Machine Learning
, pp. 1065-1072
-
-
Yang, X.1
Fu, H.2
Zha, H.3
Barlow, J.4
|