-
3
-
-
36849028220
-
Active semi-supervision for pairwise constrained clustering
-
S. Basu, A. Banerjee, and R. J. Mooney. Active semi-supervision for pairwise constrained clustering. In ICDM '04, 2004.
-
(2004)
ICDM '04
-
-
Basu, S.1
Banerjee, A.2
Mooney, R.J.3
-
4
-
-
12244300524
-
A probabilistic framework for semi-supervised clustering
-
S. Basu, M. Bilenko, and R. J. Mooney. A probabilistic framework for semi-supervised clustering. In SIGKDD '04, 2004.
-
(2004)
SIGKDD '04
-
-
Basu, S.1
Bilenko, M.2
Mooney, R.J.3
-
6
-
-
0005943240
-
Constrained k-means clustering
-
Technical Report 2000-65, Microsoft Research, May
-
K. Bennett, P. Bradley, and A. Demiriz. Constrained k-means clustering. Technical Report 2000-65, Microsoft Research, May 2000.
-
(2000)
-
-
Bennett, K.1
Bradley, P.2
Demiriz, A.3
-
7
-
-
84880095768
-
Clustering under constraints: Feasibility results and the k-means algorithm
-
I. Davidson and S. Ravi. Clustering under constraints: Feasibility results and the k-means algorithm. In SIAM Data Mining Conference, 2005.
-
(2005)
SIAM Data Mining Conference
-
-
Davidson, I.1
Ravi, S.2
-
10
-
-
0031211090
-
A decision-theoretic generalization of on-line learning and an application to boosting
-
Y. Freund and R. E. Schapire. A decision-theoretic generalization of on-line learning and an application to boosting. Journal of Computer and System Sciences, 55(1):119-139, 1997.
-
(1997)
Journal of Computer and System Sciences
, vol.55
, Issue.1
, pp. 119-139
-
-
Freund, Y.1
Schapire, R.E.2
-
12
-
-
34548564268
-
A framework for semi-supervised learning based on subjective and objective clustering criteria
-
M. Halkidi, D. Gunopulos, N. Kumar, M. Vazirgiannis, and C. Domeniconi. A framework for semi-supervised learning based on subjective and objective clustering criteria. In ICDM '05, 2005.
-
(2005)
ICDM '05
-
-
Halkidi, M.1
Gunopulos, D.2
Kumar, N.3
Vazirgiannis, M.4
Domeniconi, C.5
-
13
-
-
14344265725
-
Boosting margin based distance functions for clustering
-
T. Hertz, A. Bar-Hillel, and D. Weinshall. Boosting margin based distance functions for clustering. In ICML '04, 2004.
-
(2004)
ICML '04
-
-
Hertz, T.1
Bar-Hillel, A.2
Weinshall, D.3
-
14
-
-
33749239457
-
Learning a kernel function for classification with small training samples
-
T. Hertz, A. B. Hillel, and D. Weinshall. Learning a kernel function for classification with small training samples. In ICML '06, 2006.
-
(2006)
ICML '06
-
-
Hertz, T.1
Hillel, A.B.2
Weinshall, D.3
-
15
-
-
33845594193
-
Learning distance metrics with contextual constraints for image retrieval
-
S. C. H. Hoi, W. Liu, M. R. Lyu, and W.-Y. Ma. Learning distance metrics with contextual constraints for image retrieval. In CVPR '06, 2006.
-
(2006)
CVPR '06
-
-
Hoi, S.C.H.1
Liu, W.2
Lyu, M.R.3
Ma, W.-Y.4
-
16
-
-
84893405732
-
Data clustering: A review
-
September
-
A. K. Jain, M. N. Murty, and P. J. Flynn. Data clustering: a review. A CM Comput. Surv., 31(3):264-323, September 1999.
-
(1999)
A CM Comput. Surv
, vol.31
, Issue.3
, pp. 264-323
-
-
Jain, A.K.1
Murty, M.N.2
Flynn, P.J.3
-
18
-
-
9444294778
-
From instance-level constraints to space-level constraints: Making the most of prior knowledge in data clustering
-
D. Klein, S. D. Kamvar, and C. D. Manning. From instance-level constraints to space-level constraints: Making the most of prior knowledge in data clustering. In ICML'02, 2002.
-
(2002)
ICML'02
-
-
Klein, D.1
Kamvar, S.D.2
Manning, C.D.3
-
20
-
-
1942516950
-
Learning with idealized kernels
-
J. T. Kwok and I. W. Tsang. Learning with idealized kernels. In ICML '03, 2003.
-
(2003)
ICML '03
-
-
Kwok, J.T.1
Tsang, I.W.2
-
22
-
-
84880128402
-
Model-based clustering with probabilistic constraints
-
M. H. C. Law, A. P. Topchy, and A. K. Jain. Model-based clustering with probabilistic constraints. In SDM '05, 2005.
-
(2005)
SDM '05
-
-
Law, M.H.C.1
Topchy, A.P.2
Jain, A.K.3
-
23
-
-
84898984833
-
Semi-supervised learning with penalized probabilistic clustering
-
Z. Lu and T. Leen. Semi-supervised learning with penalized probabilistic clustering. In NIPS '05, 2005.
-
(2005)
NIPS '05
-
-
Lu, Z.1
Leen, T.2
-
24
-
-
84899013108
-
On spectral clustering: Analysis and an algorithm
-
A. Y. Ng, M. I. Jordan, and Y. Weiss. On spectral clustering: Analysis and an algorithm. In NIPS '01, 2001.
-
(2001)
NIPS '01
-
-
Ng, A.Y.1
Jordan, M.I.2
Weiss, Y.3
-
25
-
-
84898997673
-
Learning a distance metric from relative comparisons
-
M. Schultz and T. Joachims. Learning a distance metric from relative comparisons. In NIPS '03, 2003.
-
(2003)
NIPS '03
-
-
Schultz, M.1
Joachims, T.2
-
28
-
-
33749257955
-
Distance metric learning for large margin nearest neighbor classification
-
K. Weinberger, J. Blitzer, and L. Saul. Distance metric learning for large margin nearest neighbor classification. In NIPS '06, 2006.
-
(2006)
NIPS '06
-
-
Weinberger, K.1
Blitzer, J.2
Saul, L.3
-
29
-
-
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 NIPS '03, 2003.
-
(2003)
NIPS '03
-
-
Xing, E.P.1
Ng, A.Y.2
Jordan, M.I.3
Russell, S.4
-
30
-
-
35148844074
-
An efficient algorithm for local distance metric learning
-
L. Yang, R. Jin, R. Sukthankar, and Y. Liu. An efficient algorithm for local distance metric learning. In AAAI '06, 2006.
-
(2006)
AAAI '06
-
-
Yang, L.1
Jin, R.2
Sukthankar, R.3
Liu, Y.4
-
31
-
-
85024373635
-
A re-examination of text categorization methods
-
Y. Yang and X. Liu. A re-examination of text categorization methods. In SIGIR '99, 1999.
-
(1999)
SIGIR '99
-
-
Yang, Y.1
Liu, X.2
-
32
-
-
84880784532
-
Parametric distance metric learning with label information
-
Z. Zhang, J. Kwok, and D. Yeung. Parametric distance metric learning with label information. In IJCAI'03, 2003.
-
(2003)
IJCAI'03
-
-
Zhang, Z.1
Kwok, J.2
Yeung, D.3
|