-
1
-
-
54249110594
-
Mixed membership stochastic blockmodels
-
June
-
E. M. Airoldi, D. M. Blei, S. E. Fienberg, and E. P. Xing. Mixed membership stochastic blockmodels. J. Mach. Learn. Res., 9:1981-2014, June 2008.
-
(2008)
J. Mach. Learn. Res.
, vol.9
, pp. 1981-2014
-
-
Airoldi, E.M.1
Blei, D.M.2
Fienberg, S.E.3
Xing, E.P.4
-
2
-
-
26244461684
-
Clustering with bregman divergences
-
December
-
A. Banerjee, S. Merugu, I. S. Dhillon, and J. Ghosh. Clustering with bregman divergences. J. Mach. Learn. Res., 6:1705-1749, December 2005.
-
(2005)
J. Mach. Learn. Res.
, vol.6
, pp. 1705-1749
-
-
Banerjee, A.1
Merugu, S.2
Dhillon, I.S.3
Ghosh, J.4
-
3
-
-
21844457672
-
Learning a mahalanobis metric from equivalence constraints
-
A. Bar-Hillel, T. Hertz, N. Shental, and D. Weinshall. Learning a mahalanobis metric from equivalence constraints. JMLR, 6, 2005.
-
(2005)
JMLR
, vol.6
-
-
Bar-Hillel, A.1
Hertz, T.2
Shental, N.3
Weinshall, D.4
-
5
-
-
12244300524
-
A probabilistic framework for semi-supervised clustering
-
S. Basu, M. Bilenko, and R. J. Mooney. A probabilistic framework for semi-supervised clustering. KDD '04, pages 59-68, 2004.
-
(2004)
KDD '04
, pp. 59-68
-
-
Basu, S.1
Bilenko, M.2
Mooney, R.J.3
-
6
-
-
14344264451
-
Integrating constraints and metric learning in semi-supervised clustering
-
M. Bilenko, S. Basu, and R. J. Mooney. Integrating constraints and metric learning in semi-supervised clustering. In ICML '04, 2004.
-
(2004)
ICML '04
-
-
Bilenko, M.1
Basu, S.2
Mooney, R.J.3
-
7
-
-
0038589432
-
Learning to probabilistically identify authoritative documents
-
D. Cohn and H. Chang. Learning to probabilistically identify authoritative documents. In ICML '00, pages 167-174, 2000.
-
(2000)
ICML '00
, pp. 167-174
-
-
Cohn, D.1
Chang, H.2
-
8
-
-
2942723846
-
A divisive information-theoretic feature clustering algorithm for text classification
-
I. S. Dhillon, S. Mallela, and R. Kumar. A divisive information-theoretic feature clustering algorithm for text classification. JMLR, 3:1265-1287, 2003.
-
(2003)
JMLR
, vol.3
, pp. 1265-1287
-
-
Dhillon, I.S.1
Mallela, S.2
Kumar, R.3
-
9
-
-
33745561205
-
An introduction to variable and feature selection
-
Mar.
-
I. Guyon and A. Elisseeff. An introduction to variable and feature selection. J. Mach. Learn. Res., 3:1157-1182, Mar. 2003.
-
(2003)
J. Mach. Learn. Res.
, vol.3
, pp. 1157-1182
-
-
Guyon, I.1
Elisseeff, A.2
-
10
-
-
85026972772
-
Probabilistic latent semantic indexing
-
T. Hofmann. Probabilistic latent semantic indexing. SIGIR '99, pages 50-57, 1999.
-
(1999)
SIGIR '99
, pp. 50-57
-
-
Hofmann, T.1
-
11
-
-
31844447616
-
Semi-supervised graph clustering: A kernel approach
-
B. Kulis, S. Basu, I. Dhillon, and R. Mooney. Semi-supervised graph clustering: a kernel approach. ICML '05, pages 457-464, 2005.
-
(2005)
ICML '05
, pp. 457-464
-
-
Kulis, B.1
Basu, S.2
Dhillon, I.3
Mooney, R.4
-
12
-
-
84898964201
-
Algorithms for non-negative matrix factorization
-
D. D. Lee and H. S. Seung. Algorithms for non-negative matrix factorization. In NIPS '00, pages 556-562, 2000.
-
(2000)
NIPS '00
, pp. 556-562
-
-
Lee, D.D.1
Seung, H.S.2
-
13
-
-
34250765347
-
Spectral clustering for multi-type relational data
-
B. Long, Z. (mark Zhang, X. Wu, and P. S. Yu. Spectral clustering for multi-type relational data. In ICML '06, pages 585-592, 2006.
-
(2006)
ICML '06
, pp. 585-592
-
-
Long Z, B.1
Zhang, M.2
Wu, X.3
Yu, P.S.4
-
14
-
-
36849020504
-
A probabilistic framework for relational clustering
-
B. Long, Z. M. Zhang, and P. S. Yu. A probabilistic framework for relational clustering. In KDD '07, pages 470-479, 2007.
-
(2007)
KDD '07
, pp. 470-479
-
-
Long, B.1
Zhang, Z.M.2
Yu, P.S.3
-
15
-
-
34548583274
-
A tutorial on spectral clustering
-
December
-
U. Luxburg. A tutorial on spectral clustering. Statistics and Computing, 17:395-416, December 2007.
-
(2007)
Statistics and Computing
, vol.17
, pp. 395-416
-
-
Luxburg, U.1
-
17
-
-
37649028224
-
Finding and evaluating community structure in networks
-
M. E. J. Newman and M. Girvan. Finding and evaluating community structure in networks. Physical Review E (Statistical, Nonlinear, and Soft Matter Physics), 69(2), 2004.
-
(2004)
Physical Review E (Statistical, Nonlinear, and Soft Matter Physics)
, vol.69
, Issue.2
-
-
Newman, M.E.J.1
Girvan, M.2
-
18
-
-
49749128817
-
Consensus-based ensembles of soft clusterings
-
August
-
K. Punera and J. Ghosh. Consensus-based ensembles of soft clusterings. Appl. Artif. Intell., 22:780-810, August 2008.
-
(2008)
Appl. Artif. Intell.
, vol.22
, pp. 780-810
-
-
Punera, K.1
Ghosh, J.2
-
20
-
-
0041965980
-
Cluster ensembles - A knowledge reuse framework for combining multiple partitions
-
A. Strehl, J. Ghosh, and C. Cardie. Cluster ensembles - a knowledge reuse framework for combining multiple partitions. Journal of Machine Learning Research, 3:583-617, 2002.
-
(2002)
Journal of Machine Learning Research
, vol.3
, pp. 583-617
-
-
Strehl, A.1
Ghosh, J.2
Cardie, C.3
-
21
-
-
83255185987
-
Pathsim: Meta path-based top-k similarity search in heterogeneous information networks
-
Y. Sun, J. Han, X. Yan, P. S. Yu, and T. Wu. Pathsim: Meta path-based top-k similarity search in heterogeneous information networks. In VLDB '11, 2011.
-
(2011)
VLDB '11
-
-
Sun, Y.1
Han, J.2
Yan, X.3
Yu, P.S.4
Wu, T.5
-
22
-
-
70349121194
-
Rankclus: Integrating clustering with ranking for heterogeneous information network analysis
-
Y. Sun, J. Han, P. Zhao, Z. Yin, H. Cheng, and T. Wu. Rankclus: integrating clustering with ranking for heterogeneous information network analysis. In EDBT '09, pages 565-576, 2009.
-
(2009)
EDBT '09
, pp. 565-576
-
-
Sun, Y.1
Han, J.2
Zhao, P.3
Yin, Z.4
Cheng, H.5
Wu, T.6
-
23
-
-
70350625449
-
Ranking-based clustering of heterogeneous information networks with star network schema
-
Y. Sun, Y. Yu, and J. Han. Ranking-based clustering of heterogeneous information networks with star network schema. In KDD '09, pages 797-806, 2009.
-
(2009)
KDD '09
, pp. 797-806
-
-
Sun, Y.1
Yu, Y.2
Han, J.3
-
24
-
-
80055028173
-
Community discovery using nonnegative matrix factorization
-
F.Wang, T. Li, X. Wang, S. Zhu, and C. Ding. Community discovery using nonnegative matrix factorization. Data Mining and Knowledge Discovery, 20, 2010.
-
(2010)
Data Mining and Knowledge Discovery
, vol.20
-
-
Wang, F.1
Li, T.2
Wang, X.3
Zhu, S.4
Ding, C.5
-
25
-
-
57149125154
-
Csv: Visualizing and mining cohesive subgraphs
-
N. Wang, S. Parthasarathy, K.-L. Tan, and A. K. H. Tung. Csv: visualizing and mining cohesive subgraphs. In SIGMOD '08, pages 445-458, 2008.
-
(2008)
SIGMOD '08
, pp. 445-458
-
-
Wang, N.1
Parthasarathy, S.2
Tan, K.-L.3
Tung, A.K.H.4
-
26
-
-
36949010345
-
Scan: A structural clustering algorithm for networks
-
X. Xu, N. Yuruk, Z. Feng, and T. A. J. Schweiger. Scan: a structural clustering algorithm for networks. In KDD '07, pages 824-833, 2007.
-
(2007)
KDD '07
, pp. 824-833
-
-
Xu, X.1
Yuruk, N.2
Feng, Z.3
Schweiger, T.A.J.4
-
27
-
-
77954565155
-
Discriminative semi-supervised feature selection via manifold regularization
-
July
-
Z. Xu, I. King, M. R.-T. Lyu, and R. Jin. Discriminative semi-supervised feature selection via manifold regularization. Trans. Neur. Netw., 21:1033-1047, July 2010.
-
(2010)
Trans. Neur. Netw.
, vol.21
, pp. 1033-1047
-
-
Xu, Z.1
King, I.2
Lyu, M.R.-T.3
Jin, R.4
-
29
-
-
34547989065
-
Semi-supervised feature selection via spectral analysis
-
Z. Zhao and H. Liu. Semi-supervised feature selection via spectral analysis. In ICDM '07, 2007.
-
(2007)
ICDM '07
-
-
Zhao, Z.1
Liu, H.2
-
31
-
-
1942484430
-
Semi-Supervised learning using gaussian fields and harmonic functions
-
X. Zhu, Z. Ghahramani, and J. D. Lafferty. Semi-Supervised learning using gaussian fields and harmonic functions. In ICML '03, pages 912-919, 2003.
-
(2003)
ICML '03
, pp. 912-919
-
-
Zhu, X.1
Ghahramani, Z.2
Lafferty, J.D.3
|