-
1
-
-
84893405732
-
Data clustering: A review
-
DD, Sep
-
A. K. Jain, M. N. Murty, and P. J. Flynn, "Data clustering: A review," ACM Comput. Surv., vol. 31. no. 3. DD. 264-323. Sep. 1999.
-
(1999)
ACM Comput. Surv
, vol.31
, Issue.3
, pp. 264-323
-
-
Jain, A.K.1
Murty, M.N.2
Flynn, P.J.3
-
3
-
-
64049106765
-
-
K. Wagstaff, C. Cardie, S. Rogers, and S. Schroedl, Constrained K-means clustering with background knowledge in Proc. Int. Conf. Mach Learn., 2001, pp. 577-584.
-
K. Wagstaff, C. Cardie, S. Rogers, and S. Schroedl, "Constrained K-means clustering with background knowledge in Proc. Int. Conf. Mach Learn., 2001, pp. 577-584.
-
-
-
-
5
-
-
0031257480
-
Fuzzy clustering with partial supervision
-
Oct
-
W. Pedrycz and J. Waletzky, "Fuzzy clustering with partial supervision," IEEE Trans. Syst., Man, Cybern. B, Cybern., vol. 27, no. 5, pp. 787-795, Oct. 1997.
-
(1997)
IEEE Trans. Syst., Man, Cybern. B, Cybern
, vol.27
, Issue.5
, pp. 787-795
-
-
Pedrycz, W.1
Waletzky, J.2
-
6
-
-
12244300524
-
A probabilistic framework for semi-supervised clustering
-
S. Basu, A. Banerjee, and R. J. Mooney, "A probabilistic framework for semi-supervised clustering," in Proc. ACM SIGKDD Int. Conf. Knowl. Discovery Data Mining, 2005, pp. 59-68.
-
(2005)
Proc. ACM SIGKDD Int. Conf. Knowl. Discovery Data Mining
, pp. 59-68
-
-
Basu, S.1
Banerjee, A.2
Mooney, R.J.3
-
7
-
-
85133386144
-
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 Proc. Int. Conf. Mach. Learn., 2003, pp. 505-512.
-
(2003)
Proc. Int. Conf. Mach. Learn
, pp. 505-512
-
-
Xing, E.P.1
Ng, A.Y.2
Jordan, M.I.3
Russell, S.4
-
8
-
-
33646084850
-
Locally linear metric adaptation with application to semi-supervised clustering and image retrieval
-
Jul
-
H. Chang and D. Y. Yeung, "Locally linear metric adaptation with application to semi-supervised clustering and image retrieval," Pattern Recognit., vol. 39, no. 7, pp. 1253-1264, Jul. 2006.
-
(2006)
Pattern Recognit
, vol.39
, Issue.7
, pp. 1253-1264
-
-
Chang, H.1
Yeung, D.Y.2
-
9
-
-
21144437828
-
Intelligent clustering with instance-level constraints,
-
Ph.D. dissertation, Cornell Univ, Ithaca, NY
-
K. L. Wagstaff, "Intelligent clustering with instance-level constraints," Ph.D. dissertation, Cornell Univ., Ithaca, NY, 2002.
-
(2002)
-
-
Wagstaff, K.L.1
-
10
-
-
84880095768
-
Clustering with constraints: Feasibility issues and the K-means algorithm
-
I. Davidson and S. S. Ravi, "Clustering with constraints: Feasibility issues and the K-means algorithm," in Proc. SIAM Int. Conf. Data Mining, 2005.
-
(2005)
Proc. SIAM Int. Conf. Data Mining
-
-
Davidson, I.1
Ravi, S.S.2
-
11
-
-
21844457672
-
Learning a Mahalanobis metric from equivalence constraints
-
Dec
-
A. Bar-Hillel, T. Hertz, N. Shental, and D. Weinshall, "Learning a Mahalanobis metric from equivalence constraints," J. Mach. Learn. Res., vol. 6, pp. 937-965, Dec. 2005.
-
(2005)
J. Mach. Learn. Res
, vol.6
, pp. 937-965
-
-
Bar-Hillel, A.1
Hertz, T.2
Shental, N.3
Weinshall, D.4
-
12
-
-
64049099700
-
Clustering with soft and group constraints
-
M. Law, A. Topchy, and A. K. Jain, "Clustering with soft and group constraints," in Proc. SIAM Int. Conf. Data Mining, 2005, pp. 662-670.
-
(2005)
Proc. SIAM Int. Conf. Data Mining
, pp. 662-670
-
-
Law, M.1
Topchy, A.2
Jain, A.K.3
-
13
-
-
84898984833
-
Semi-supervised learning with penalized probabilistic clustering
-
Cambridge, MA: MIT Press
-
Z. Lu and T. Leen, "Semi-supervised learning with penalized probabilistic clustering," in Advances in Neural Information Processing System. Cambridge, MA: MIT Press, 2005, pp. 849-856.
-
(2005)
Advances in Neural Information Processing System
, pp. 849-856
-
-
Lu, Z.1
Leen, T.2
-
14
-
-
9444294778
-
From instance-level constraints to space-level constraints: Making the most of prior knowledge in data clustering
-
D. Klein, S. Kamvar, and C. Manning, "From instance-level constraints to space-level constraints: Making the most of prior knowledge in data clustering," in Proc. Int. Conf. Mach. Learn., 2002, pp. 307-313.
-
(2002)
Proc. Int. Conf. Mach. Learn
, pp. 307-313
-
-
Klein, D.1
Kamvar, S.2
Manning, C.3
-
15
-
-
9444230302
-
-
Cornell Univ, Ithaca, NY, Tech. Rep. TR2003-1892
-
D. Cohn, R. Caruana, and A. McCallum, "Semi-supervised clustering with user feedback," Cornell Univ., Ithaca, NY, Tech. Rep. TR2003-1892, 2003.
-
(2003)
Semi-supervised clustering with user feedback
-
-
Cohn, D.1
Caruana, R.2
McCallum, A.3
-
16
-
-
34047097838
-
Semi-supervised clustering: Probabilistic models, algorithms and experiments,
-
Ph.D. dissertation, Dept. Comput. Sci, Univ. Texas Austin, Austin, TX
-
S. Basu, "Semi-supervised clustering: Probabilistic models, algorithms and experiments," Ph.D. dissertation, Dept. Comput. Sci., Univ. Texas Austin, Austin, TX, 2005.
-
(2005)
-
-
Basu, S.1
-
17
-
-
0031209604
-
Selective sampling using the query by committee algorithm
-
Aug./Sep
-
Y. Freund, H. S. Seung, E. Shamir, and N. Tishby, "Selective sampling using the query by committee algorithm," Mach. Learn., vol. 28, no. 2/3, pp. 133-168, Aug./Sep. 1997.
-
(1997)
Mach. Learn
, vol.28
, Issue.2-3
, pp. 133-168
-
-
Freund, Y.1
Seung, H.S.2
Shamir, E.3
Tishby, N.4
-
18
-
-
24644505329
-
Pruning training sets for learning of object categories
-
A. Angelove, Y. Abu-Mostafa, and P. Perona, "Pruning training sets for learning of object categories," in Proc. IEEE Conf. Comput. Vis. Pattern Recog., 2005, pp. 494-501.
-
(2005)
Proc. IEEE Conf. Comput. Vis. Pattern Recog
, pp. 494-501
-
-
Angelove, A.1
Abu-Mostafa, Y.2
Perona, P.3
-
19
-
-
0032139235
-
The random subspace method for constructing decision forests
-
Aug
-
T. K. Ho, "The random subspace method for constructing decision forests," IEEE Trans. Pattern Anal. Mach. Intell., vol. 20, no. 8, pp. 832-844, Aug. 1998.
-
(1998)
IEEE Trans. Pattern Anal. Mach. Intell
, vol.20
, Issue.8
, pp. 832-844
-
-
Ho, T.K.1
-
20
-
-
84950632109
-
Objective criteria for the evaluation of clustering methods
-
Dec
-
W. M. Rand, "Objective criteria for the evaluation of clustering methods," J. Amer. Stat. Assoc., vol. 66, no. 336, pp. 846-850, Dec. 1971.
-
(1971)
J. Amer. Stat. Assoc
, vol.66
, Issue.336
, pp. 846-850
-
-
Rand, W.M.1
-
21
-
-
44649105615
-
Unsupervised feature selection using clustering ensembles and population based incremental learning algorithm
-
Sep
-
Y. Hong, S. Kwong, Y. Chang, and Q. Ren, "Unsupervised feature selection using clustering ensembles and population based incremental learning algorithm," Pattern Recognit., vol. 41, no. 9, pp. 2747-2756, Sep. 2008.
-
(2008)
Pattern Recognit
, vol.41
, Issue.9
, pp. 2747-2756
-
-
Hong, Y.1
Kwong, S.2
Chang, Y.3
Ren, Q.4
-
22
-
-
38749139222
-
Consensus unsupervised feature ranking from multiple views
-
Apr
-
Y. Hong, S. Kwong, Y. Chang, and Q. Ren, "Consensus unsupervised feature ranking from multiple views," Pattern Recognit. Lett., vol. 29, no. 5, pp. 595-602, Apr. 2008.
-
(2008)
Pattern Recognit. Lett
, vol.29
, Issue.5
, pp. 595-602
-
-
Hong, Y.1
Kwong, S.2
Chang, Y.3
Ren, Q.4
-
23
-
-
43249099468
-
To combine steady-state genetic algorithm and ensemble learning for data clustering
-
Jul
-
Y. Hong and S. Kwong, "To combine steady-state genetic algorithm and ensemble learning for data clustering," Pattern Recognit. Lett., vol. 29, no. 9, pp. 1416-1423, Jul. 2008.
-
(2008)
Pattern Recognit. Lett
, vol.29
, Issue.9
, pp. 1416-1423
-
-
Hong, Y.1
Kwong, S.2
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