-
2
-
-
33749317042
-
Learning spectral clustering, with application to speech separation
-
F. R. Bach and M. I. Jordan. Learning spectral clustering, with application to speech separation. Journal of Machine Learning Research, 7:1963-2001, 2006.
-
(2006)
Journal of Machine Learning Research
, vol.7
, pp. 1963-2001
-
-
Bach, F.R.1
Jordan, M.I.2
-
4
-
-
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
-
5
-
-
84947205653
-
-
K. S. Beyer, J. Goldstein, R. Ramakrishnan, and U. Shaft. When is nearest neighbor meaningful? In International Conference on Database Theory, pages 217-235, 1999.
-
(1999)
When Is Nearest Neighbor Meaningful? in International Conference on Database Theory
, pp. 217-235
-
-
Beyer, K.S.1
Goldstein, J.2
Ramakrishnan, R.3
Shaft, U.4
-
6
-
-
33749252873
-
-
MIT Press, Cambridge, MA
-
O. Chapelle, B. Schölkopf, and A. Zien. Semi- Supervised Learning. MIT Press, Cambridge, MA, 2006.
-
(2006)
Semi- Supervised Learning
-
-
Chapelle, O.1
Schölkopf, B.2
Zien, A.3
-
7
-
-
36849021609
-
Nonlinear adaptive distance metric learning for clustering
-
J. H. Chen, Z. Zhao, J. P. Ye, and H. Liu. Nonlinear adaptive distance metric learning for clustering. In ACM SIGKDD Intn'l Conference on Knowledge Discovery and Data Mining, pages 123-132, 2007.
-
(2007)
ACM SIGKDD Intn'l Conference on Knowledge Discovery and Data Mining
, pp. 123-132
-
-
Chen, J.H.1
Zhao, Z.2
Ye, J.P.3
Liu, H.4
-
8
-
-
71149084539
-
Fitting a graph to vector data
-
Montreal, June
-
S. I. Daitch, J. A. Kelner, and D. A. Spielman. Fitting a graph to vector data. In Proceedings of the 26th International Conference on Machine Learning, pages 201-208, Montreal, June 2009.
-
(2009)
Proceedings of the 26th International Conference on Machine Learning
, pp. 201-208
-
-
Daitch, S.I.1
Kelner, J.A.2
Spielman, D.A.3
-
9
-
-
12244256379
-
Kernel k-means, spectral clustering and normalized cuts
-
I. S. Dhillon, Y. Guan, and B. Kulis. Kernel k-means, spectral clustering and normalized cuts. In Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 551-556, 2004.
-
(2004)
Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
, pp. 551-556
-
-
Dhillon, I.S.1
Guan, Y.2
Kulis, B.3
-
14
-
-
33646528415
-
Measuring statistical dependence with Hilbert-Schmidt norms
-
A. Gretton, O. Bousquet, A. Smola, and B. Scholkopf. Measuring statistical dependence with Hilbert-Schmidt norms. 16th International Conf. Algorithmic Learning Theory, pages 63-77, 2005.
-
(2005)
16th International Conf. Algorithmic Learning Theory
, pp. 63-77
-
-
Gretton, A.1
Bousquet, O.2
Smola, A.3
Scholkopf, B.4
-
15
-
-
26444566340
-
Contour regression: A general approach to dimension reduction
-
B. Li, H. Zha, and F. Chiaramonte. Contour regression: A general approach to dimension reduction. The Annals of Statistics, 33:1580-1616, 2005.
-
(2005)
The Annals of Statistics
, vol.33
, pp. 1580-1616
-
-
Li, B.1
Zha, H.2
Chiaramonte, F.3
-
17
-
-
34548583274
-
A tutorial on spectral clustering
-
U. V. Luxburg. A tutorial on spectral clustering. Statistics and Computing, 5:395-416, 2007.
-
(2007)
Statistics and Computing
, vol.5
, pp. 395-416
-
-
Luxburg, U.V.1
-
18
-
-
0033337021
-
Fisher discriminant analysis with kernels
-
IEEE
-
S. Mika, G. Rätsch, J. Weston, B. Schölkopf, and K. R. Müller. Fisher discriminant analysis with kernels. Neural Networks for Signal Processing IX, IEEE, pages 41-48, 1999.
-
(1999)
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
-
20
-
-
0041875229
-
On spectral clustering: Analysis and an algorithm
-
A. Y. Ng, M. I. Jordan, and Y. Weiss. On spectral clustering: Analysis and an algorithm. In Advances in Neural Information Processing Systems, volume 14, pages 849-856, 2001.
-
(2001)
Advances in Neural Information Processing Systems
, vol.14
, pp. 849-856
-
-
Ng, A.Y.1
Jordan, M.I.2
Weiss, Y.3
-
23
-
-
0034704222
-
Nonlinear dimensionality reduction by locally linear embedding
-
S. Roweis and L. 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.1
Saul, L.2
-
25
-
-
34547972314
-
A dependence maximization view of clustering
-
L. Song, A. J. Smola, A. Gretton, and K. M. Borgwardt. A dependence maximization view of clustering. In Proceedings of the 24th International Conference on Machine Learning (ICML), pages 815-822, 2007.
-
(2007)
Proceedings of the 24th International Conference on Machine Learning (ICML)
, pp. 815-822
-
-
Song, L.1
Smola, A.J.2
Gretton, A.3
Borgwardt, K.M.4
-
26
-
-
0041965980
-
Cluster ensembles-a knowledge reuse framework for combining multiple partitions
-
A. Strehl and J. Ghosh. Cluster ensembles-a knowledge reuse framework for combining multiple partitions. Journal on Machine Learning Research, 3:583-617, 2002.
-
(2002)
Journal on Machine Learning Research
, vol.3
, pp. 583-617
-
-
Strehl, A.1
Ghosh, J.2
-
27
-
-
0034704229
-
A global geometric framework for nonlinear dimensionality reduction
-
J. B. Tenenbaum, V. 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
Silva, V.2
Langford, J.C.3
-
28
-
-
84879571292
-
Distance metric learning, with application to clustering with side information
-
E. P. Xing, A. Y. Ng, M. I. Jordan, and S. Russell. Distance metric learning, with application to clustering with side information. In Advances in Neural Information Processing Systems, 15, pages 505-512, 2003.
-
(2003)
Advances in Neural Information Processing Systems
, vol.15
, pp. 505-512
-
-
Xing, E.P.1
Ng, A.Y.2
Jordan, M.I.3
Russell, S.4
-
29
-
-
0034800371
-
Principal component analysis for clustering gene expression data
-
K. Yeung and W. Ruzzo. Principal component analysis for clustering gene expression data. Bioinformatics, 17:763-774, 2001.
-
(2001)
Bioinformatics
, vol.17
, pp. 763-774
-
-
Yeung, K.1
Ruzzo, W.2
-
30
-
-
59349084916
-
Multiway spectral clustering: A margin-based perspective
-
Z. Zhang and M. I. Jordan. Multiway spectral clustering: A margin-based perspective. Statistical Science, 23:383-403, 2008.
-
(2008)
Statistical Science
, vol.23
, pp. 383-403
-
-
Zhang, Z.1
Jordan, M.I.2
|