-
2
-
-
0042378381
-
Laplacian eigenmaps for dimensionality reduction and data representation
-
M. Belkin and P. Niyogi. Laplacian eigenmaps for dimensionality reduction and data representation. Neural computation, 15(6):1373-1396, 2003.
-
(2003)
Neural Computation
, vol.15
, Issue.6
, pp. 1373-1396
-
-
Belkin, M.1
Niyogi, P.2
-
3
-
-
4344599431
-
Learning eigenfunctions links spectral embedding and kernel pca
-
Y. Bengio, O. Delalleau, N.L. Roux, J.F. Paiement, P. Vincent, and M. Ouimet. Learning eigenfunctions links spectral embedding and kernel pca. Neural Computation, 16(10):2197-2219, 2004.
-
(2004)
Neural Computation
, vol.16
, Issue.10
, pp. 2197-2219
-
-
Bengio, Y.1
Delalleau, O.2
Roux, N.L.3
Paiement, J.F.4
Vincent, P.5
Ouimet, M.6
-
4
-
-
33947233031
-
Out-of-sample extensions for lle, isomap, mds, eigenmaps, and spectral clustering
-
Y. Bengio, J.F. Paiement, and al. Out-of-sample extensions for lle, isomap, mds, eigenmaps, and spectral clustering. Advances in neural information processing systems, 16:177-184, 2004.
-
(2004)
Advances in Neural Information Processing Systems
, vol.16
, pp. 177-184
-
-
Bengio, Y.1
Paiement, J.F.2
-
6
-
-
33847676413
-
Statistical properties of kernel principal component analysis
-
G. Blanchard, O. Bousquet, and L. Zwald. Statistical properties of kernel principal component analysis. Machine Learning, 66(2):259-294, 2007.
-
(2007)
Machine Learning
, vol.66
, Issue.2
, pp. 259-294
-
-
Blanchard, G.1
Bousquet, O.2
Zwald, L.3
-
10
-
-
0037948870
-
Hessian eigenmaps: Locally linear embedding techniques for highdimensional data
-
D.L. Donoho and C. Grimes. Hessian eigenmaps: Locally linear embedding techniques for highdimensional data. Proceedings of the National Academy of Sciences, 100(10):5591-5596, 2003.
-
(2003)
Proceedings of the National Academy of Sciences
, vol.100
, Issue.10
, pp. 5591-5596
-
-
Donoho, D.L.1
Grimes, C.2
-
11
-
-
11144299132
-
A kernel view of the dimensionality reduction of manifolds
-
ACM
-
J. Ham, D.D. Lee, S. Mika, and B. Schölkopf. A kernel view of the dimensionality reduction of manifolds. In Proceedings of the twenty-first international conference on Machine learning, page 47. ACM, 2004.
-
(2004)
Proceedings of the Twenty-first International Conference on Machine Learning
, pp. 47
-
-
Ham, J.1
Lee, D.D.2
Mika, S.3
Schölkopf, B.4
-
13
-
-
77958550281
-
K-dimensional coding schemes in hilbert spaces
-
Andreas Maurer and Massimiliano Pontil. K-dimensional coding schemes in hilbert spaces. IEEE Transactions on Information Theory, 56(11):5839-5846, 2010.
-
(2010)
IEEE Transactions on Information Theory
, vol.56
, Issue.11
, pp. 5839-5846
-
-
Maurer, A.1
Pontil, M.2
-
14
-
-
0001638327
-
Optimum bounds for the distributions of martingales in banach spaces
-
Iosif Pinelis. Optimum bounds for the distributions of martingales in banach spaces. The Annals of Probability, pages 1679-1706, 1994.
-
(1994)
The Annals of Probability
, pp. 1679-1706
-
-
Pinelis, I.1
-
15
-
-
0010853295
-
Hilbert space: Compact operators and the trace theorem
-
Cambridge University Press
-
J.R. Retherford. Hilbert Space: Compact Operators and the Trace Theorem. London Mathematical Society Student Texts. Cambridge University Press, 1993.
-
(1993)
London Mathematical Society Student Texts
-
-
Retherford, J.R.1
-
16
-
-
0034704222
-
Nonlinear dimensionality reduction by locally linear embedding
-
S.T. Roweis and L.K. Saul. Nonlinear dimensionality reduction by locally linear embedding. Science, 290(5500):2323-2326, 2000.
-
(2000)
Science
, vol.290
, Issue.5500
, pp. 2323-2326
-
-
Roweis, S.T.1
Saul, L.K.2
-
17
-
-
2342517502
-
Think globally, fit locally: Unsupervised learning of low dimensional manifolds
-
L.K. Saul and S.T. Roweis. Think globally, fit locally: unsupervised learning of low dimensional manifolds. The Journal of Machine Learning Research, 4:119-155, 2003.
-
(2003)
The Journal of Machine Learning Research
, vol.4
, pp. 119-155
-
-
Saul, L.K.1
Roweis, S.T.2
-
19
-
-
22844440983
-
On the eigenspectrum of the gram matrix and the generalization error of kernel-pca
-
J. Shawe-Taylor, C. K.Williams, N. Cristianini, and J. Kandola. On the eigenspectrum of the gram matrix and the generalization error of kernel-pca. Information Theory, IEEE Transactions on, 51(7), 2005.
-
(2005)
Information Theory IEEE Transactions on
, vol.51
, Issue.7
-
-
Shawe-Taylor, J.1
Williams, C.K.2
Cristianini, N.3
Kandola, J.4
-
21
-
-
33746329499
-
The fastest mixing markov process on a graph and a connection to a maximum variance unfolding problem
-
J. Sun, S. Boyd, L. Xiao, and P. Diaconis. The fastest mixing markov process on a graph and a connection to a maximum variance unfolding problem. SIAM review, 48(4):681-699, 2006.
-
(2006)
SIAM Review
, vol.48
, Issue.4
, pp. 681-699
-
-
Sun, J.1
Boyd, S.2
Xiao, L.3
Diaconis, P.4
-
22
-
-
0034704229
-
A global geometric framework for nonlinear dimensionality reduction
-
J.B. Tenenbaum, V. De Silva, and J.C. Langford. A global geometric framework for nonlinear dimensionality reduction. Science, 290(5500):2319-2323, 2000.
-
(2000)
Science
, vol.290
, Issue.5500
, pp. 2319-2323
-
-
Tenenbaum, J.B.1
De Silva, V.2
Langford, J.C.3
-
25
-
-
33744949513
-
Unsupervised learning of image manifolds by semidefinite programming
-
K.Q.Weinberger and L.K. Saul. Unsupervised learning of image manifolds by semidefinite programming. International Journal of Computer Vision, 70(1):77-90, 2006.
-
(2006)
International Journal of Computer Vision
, vol.70
, Issue.1
, pp. 77-90
-
-
Weinberger, K.Q.1
Saul, L.K.2
-
26
-
-
0036165146
-
On a connection between kernel pca and metric multidimensional scaling
-
C.K.I. Williams. On a connection between kernel pca and metric multidimensional scaling. Machine Learning, 46(1):11-19, 2002.
-
(2002)
Machine Learning
, vol.46
, Issue.1
, pp. 11-19
-
-
Williams, C.K.I.1
|