-
1
-
-
77950369345
-
Data clustering: 50 years beyond K-means
-
A. K. Jain, "Data clustering: 50 years beyond K-means Pattern Recogn. Lett., vol. 31, no. 8, pp. 651-666, 2010
-
(2010)
Pattern Recogn. Lett
, vol.31
, Issue.8
, pp. 651-666
-
-
Jain, A.K.1
-
2
-
-
0003922190
-
-
2nd ed. New York, NY, USA: Wiley
-
R. O. Duda, P. E. Hart, and D. G. Stork, Pattern Classification, 2nd ed. New York, NY, USA:Wiley, 2002
-
(2002)
Pattern Classification
-
-
Duda, R.O.1
Hart, P.E.2
Stork, D.G.3
-
3
-
-
10044285764
-
Landscape of clustering algorithms
-
A. K. Jain, A. Topchy, M. H. C. Law, and J. M. Buhmann, "Landscape of clustering algorithms in Proc. Int. Conf. Pattern Recogniy, 2004, vol. 1, pp. 260-263
-
(2004)
Proc. Int. Conf. Pattern Recogniy
, vol.1
, pp. 260-263
-
-
Jain, A.K.1
Topchy, A.2
Law, M.H.C.3
Buhmann, J.M.4
-
4
-
-
16444383160
-
Survey of clustering algorithms
-
May
-
R. Xu and D. Wunsch-II, "Survey of clustering algorithms IEEE Trans. Neural Netw., vol. 16, no. 3, pp. 645-678, May 2005
-
(2005)
IEEE Trans. Neural Netw
, vol.16
, Issue.3
, pp. 645-678
-
-
Xu, R.1
Wunsch-Ii, D.2
-
5
-
-
84893405732
-
Data clustering: A review
-
A. K. Jain, M. N. Murty, and P. J. Flynn, "Data clustering: A review ACM Comput. Surveys, vol. 31, no. 3, pp. 265-323, 1999
-
(1999)
ACM Comput. Surveys
, vol.31
, Issue.3
, pp. 265-323
-
-
Jain, A.K.1
Murty, M.N.2
Flynn, P.J.3
-
6
-
-
0038119396
-
Techniques of cluster algorithms in Data mining
-
J.Grabmeier andA. Rudolph, "Techniques of cluster algorithms in Data mining Data Mining and Knowl. Discov., vol. 6, no. 4, pp. 303-360, 2002
-
(2002)
Data Mining and Knowl. Discov
, vol.6
, Issue.4
, pp. 303-360
-
-
Grabmeier, J.1
Rudolph, A.2
-
7
-
-
79960693840
-
Distributed clustering using wireless sensor networks
-
Aug
-
P. A. Forero, A. Cano, and G. B. Giannakis, "Distributed clustering using wireless sensor networks IEEE J. Sel. Topics Signal Process., vol. 5, no. 4, pp. 707-724, Aug. 2011
-
(2011)
IEEE J. Sel. Topics Signal Process
, vol.5
, Issue.4
, pp. 707-724
-
-
Forero, P.A.1
Cano, A.2
Giannakis, G.B.3
-
9
-
-
62349117264
-
Consensus-based k-means algorithm for distributed learning using wireless sensor networks
-
Inf. Process., Sedona, AZ, USA, May 11-14
-
P. A. Forero, A. Cano, and G. B. Giannakis, "Consensus-based k-means algorithm for distributed learning using wireless sensor networks in Proc. Workshop Sens., Signal, Inf. Process., Sedona, AZ, USA, May 11-14, 2008
-
(2008)
Proc. Workshop Sens., Signal
-
-
Forero, P.A.1
Cano, A.2
Giannakis, G.B.3
-
10
-
-
51449105623
-
Consensus-based distributed expectation-maximization algorithm for density estimation and classification using wireless sensor networks
-
Speech, Signal Process., Las Vegas, NV, USA
-
P. A. Forero, A. Cano, and G. B. Giannakis, "Consensus-based distributed expectation-maximization algorithm for density estimation and classification using wireless sensor networks in Proc. Int. Conf. Acoust., Speech, Signal Process., Las Vegas, NV, USA, 2008, pp. 1989-1992
-
(2008)
Proc. Int. Conf. Acoust
, pp. 1989-1992
-
-
Forero, P.A.1
Cano, A.2
Giannakis, G.B.3
-
11
-
-
56449084749
-
Fully distributed em for very large datasets
-
Helsinki, Finland
-
J. Wolfe, A. Haghighi, and D. Klein, "Fully distributed EM for very large datasets in Proc. 25th Int. Conf. Mach. Learn., Helsinki, Finland, 2008, pp. 1184-1191
-
(2008)
Proc. 25th Int. Conf. Mach. Learn
, pp. 1184-1191
-
-
Wolfe, J.1
Haghighi, A.2
Klein, D.3
-
12
-
-
0042164384
-
Distributed em algorithms for density estimation and clustering in sensor networks
-
Aug
-
R. D. Nowak, "Distributed EM algorithms for density estimation and clustering in sensor networks IEEE Trans. Signal Process., vol. 51, no. 8, pp. 2245-2253, Aug. 2003
-
(2003)
IEEE Trans. Signal Process
, vol.51
, Issue.8
, pp. 2245-2253
-
-
Nowak, R.D.1
-
13
-
-
48949116234
-
Distributed EMalgorithm for Gaussian mixtures in sensor networks
-
Jul
-
D. Gu, "Distributed EMalgorithm for Gaussian mixtures in sensor networks IEEE Trans. Neural Netw., vol. 19, no. 7, pp. 1154-1166, Jul. 2008
-
(2008)
IEEE Trans. Neural Netw
, vol.19
, Issue.7
, pp. 1154-1166
-
-
Gu, D.1
-
14
-
-
26944439183
-
Scalable density-based distributed clustering
-
E. Januzaj, H. P. Kriegel, and P. Martin, "Scalable density-based distributed clustering in Proc. Knowl. Discov. Databases: PKDD 2004, 2004, vol. 19, no. 7, pp. 231-244
-
(2004)
Proc. Knowl. Discov. Databases: PKDD 2004
, vol.19
, Issue.7
, pp. 231-244
-
-
Januzaj, E.1
Kriegel, H.P.2
Martin, P.3
-
15
-
-
84880800384
-
Distributed clustering based on sampling local density estimates
-
M. Klusch, S. Lodi, and G. Moro, "Distributed clustering based on sampling local density estimates in Proc. Int. Joint Conf. Artif. Intell., 2003, pp. 485-490
-
(2003)
Proc. Int. Joint Conf. Artif. Intell
, pp. 485-490
-
-
Klusch, M.1
Lodi, S.2
Moro, G.3
-
16
-
-
85132267044
-
Distributed clustering using collective principal component analysis
-
H. Kargupta, W. Huang, S. Krishnamoorthy, and E. Johnson, "Distributed clustering using collective principal component analysis Knowl. Inf. Syst. J., vol. 3, no. 4, pp. 422-448, 2001
-
(2001)
Knowl. Inf. Syst. J.
, vol.3
, Issue.4
, pp. 422-448
-
-
Kargupta, H.1
Huang, W.2
Krishnamoorthy, S.3
Johnson, E.4
-
17
-
-
33646164394
-
Clustering distributed data streams in peer-To-peer environments
-
S. Bandyopadhyay, C. Giannella, U. Maulik, H. Kargupta, K. Liu, and S. Datta, "Clustering distributed data streams in peer-To-peer environments Inf. Sci., vol. 176, no. 14, pp. 1952-1985, 2006
-
(2006)
Inf. Sci
, vol.176
, Issue.14
, pp. 1952-1985
-
-
Bandyopadhyay, S.1
Giannella, C.2
Maulik, U.3
Kargupta, H.4
Liu, K.5
Datta, S.6
-
18
-
-
0036472386
-
Information theoretic clustering
-
Apr
-
E. Gokcay and J. C. Principe, "Information theoretic clustering IEEE Trans. Pattern Anal. Mach. Intell., vol. 24, no. 2, pp. 158-170, Apr. 2002
-
(2002)
IEEE Trans. Pattern Anal. Mach. Intell
, vol.24
, Issue.2
, pp. 158-170
-
-
Gokcay, E.1
Principe, J.C.2
-
19
-
-
11844257588
-
Information theoretic clustering: A unifying review of three recent algorithms
-
Proceedings of the 6th Nordic Signal Processing Symposium, NORSIG 2004
-
R. Jenssen, T. Eltoft, and J. C. Principe, "Information theoretic clustering: A unifying review of three recent algorithms in Proc. 6th Nordic Signal Process. Symp., Espoo, Finland, 2004, pp. 292-295. (Pubitemid 40087965
-
(2004)
Report - Helsinki University of Technology, Signal Processing Laboratory
, vol.46
, pp. 292-295
-
-
Jenssen, R.1
Eltoft, T.2
Principe, J.C.3
-
20
-
-
26244461684
-
Clustering with bregman divergences
-
A. Banerjee, S. Merugu, I. S. Dhillon, and J. Ghosh, "Clustering with Bregman Divergences J. Mach. Learn. Res., vol. 6, pp. 1705-1749, 2005
-
(2005)
J. Mach. Learn. Res
, vol.6
, pp. 1705-1749
-
-
Banerjee, A.1
Merugu, S.2
Dhillon, I.S.3
Ghosh, J.4
-
21
-
-
29444444918
-
Information based clustering
-
N. Slonim, G. S. Atwal, G. Tkacik, and W. Bialek, "Information based clustering Proc. Nat. Acad. Sci. USA, vol. 105, no. 51, pp. 18297-18302, 2005
-
(2005)
Proc. Nat. Acad. Sci. USA
, vol.105
, Issue.51
, pp. 18297-118302
-
-
Slonim, N.1
Atwal, G.S.2
Tkacik, G.3
Bialek, W.4
-
23
-
-
27144559469
-
Arobust information clustering algorithm
-
Q. Song, "Arobust information clustering algorithm Neural Comput., pp. 2672-2698, 2005
-
(2005)
Neural Comput
, pp. 2672-2698
-
-
Song, Q.1
-
24
-
-
33749545220
-
Robust informationtheoretic clustering
-
Discov. Data Mining
-
C. Bohm, C. Faloutsos, J. Y. Pan, and C. Plant, "Robust informationtheoretic clustering in Proc. 12th ACM SIGKDD Int. Conf. Knowl. Discov. Data Mining, 2005, vol. 17, no. 12, pp. 65-75
-
(2005)
Proc. 12th ACM SIGKDD Int. Conf. Knowl
, vol.17
, Issue.12
, pp. 65-75
-
-
Bohm, C.1
Faloutsos, C.2
Pan, J.Y.3
Plant, C.4
-
25
-
-
0344120262
-
Applying the information bottleneck principle to unsupervised clustering of discrete and continuous image representations
-
S. Gordon, H. Greenspan, and J. Goldberger, "Applying the information bottleneck principle to unsupervised clustering of discrete and continuous image representations in Proc. 9th IEEE Int. Conf. Comput. Vision, 2003, pp. 370-377
-
(2003)
Proc. 9th IEEE Int. Conf. Comput. Vision
, pp. 370-377
-
-
Gordon, S.1
Greenspan, H.2
Goldberger, J.3
-
26
-
-
67649845516
-
Image segmentation using information bottleneck method
-
Jul
-
A. Bardera, J. Rigau, I. Boada, M. Feixas, and M. Sbert, "Image segmentation using information bottleneck method IEEE Trans. Image Process., vol. 18, no. 7, pp. 1601-1612, Jul. 2009
-
(2009)
IEEE Trans. Image Process
, vol.18
, Issue.7
, pp. 1601-1612
-
-
Bardera, A.1
Rigau, J.2
Boada, I.3
Feixas, M.4
Sbert, M.5
-
27
-
-
0001808038
-
The information bottleneck method
-
N. Tishby, F. Pereira, and W. Bialek, "The information bottleneck method in Proc. 37th Ann. Allerton Conf. Commun., Contr. Comput., 1999, pp. 368-377
-
(1999)
Proc. 37th Ann. Allerton Conf. Commun., Contr. Comput
, pp. 368-377
-
-
Tishby, N.1
Pereira, F.2
Bialek, W.3
-
29
-
-
13544255384
-
A privacy-sensitive approach to distributed clustering
-
S. Merugu and J. Ghosh, "A privacy-sensitive approach to distributed clustering Pattern Recognit. Lett., vol. 26, no. 4, pp. 399-410, 2005
-
(2005)
Pattern Recognit. Lett
, vol.26
, Issue.4
, pp. 399-410
-
-
Merugu, S.1
Ghosh, J.2
-
30
-
-
78649884242
-
Privacy preserving distributed learning clustering of healthcare data using cryptography protocols
-
Conf. Workshops
-
A. M. Elmisery and H. Fu, "Privacy preserving distributed learning clustering of healthcare data using cryptography protocols in Proc. IEEE 34th Ann. Comput. Software and Appl. Conf. Workshops, 2010, pp. 140-145
-
(2010)
Proc. IEEE 34th Ann. Comput. Software and Appl
, pp. 140-145
-
-
Elmisery, A.M.1
Fu, H.2
-
33
-
-
0003580192
-
On estimation of a probability density function and mode
-
San Francisco, CA: Holden-Day
-
E. Parzen, "On estimation of a probability density function and mode in Time Series Analysis Papers. San Francisco, CA: Holden-Day, 1967
-
(1967)
Time Series Analysis Papers
-
-
Parzen, E.1
-
34
-
-
77955401339
-
Diffusion LMS strategies for distributed estimation
-
Mar
-
F. S. Cattivelli, C. G. Lopes, and A. H. Sayed, "Diffusion LMS strategies for distributed estimation IEEE Trans. Signal Process., vol. 58, no. 3, pp. 1035-1048, Mar. 2010
-
(2010)
IEEE Trans. Signal Process
, vol.58
, Issue.3
, pp. 1035-1048
-
-
Cattivelli, F.S.1
Lopes, C.G.2
Sayed, A.H.3
-
35
-
-
34547515577
-
Distributed processing over adaptive networks
-
Workshop, Lexington, MA, USA Jun
-
C. G. Lopes and A. H. Sayed, "Distributed processing over adaptive networks in Proc. Adapt. Sens. Array Process. Workshop, Lexington, MA, USA, Jun. 2006
-
(2006)
Proc. Adapt. Sens. Array Process
-
-
Lopes, C.G.1
Sayed, A.H.2
-
36
-
-
84880872307
-
Diffusion information theoretic learning for distributed estimation over network
-
Aug 15
-
C. Li, P. Shen, Y. Liu, and Z. Zhang, "Diffusion information theoretic learning for distributed estimation over network IEEE Trans. Signal Process., vol. 61, no. 16, pp. 4011-4024, Aug 15, 2013
-
(2013)
IEEE Trans. Signal Process
, vol.61
, Issue.16
, pp. 4011-4024
-
-
Li, C.1
Shen, P.2
Liu, Y.3
Zhang, Z.4
-
37
-
-
46649115239
-
Diffusion recursive least-squares for distributed estimation over adaptive networks
-
May
-
F. S. Cattivelli, C. G. Lopes, and A. H. Sayed, "Diffusion recursive least-squares for distributed estimation over adaptive networks IEEE Trans. Signal Process., vol. 56, no. 5, pp. 1865-1877, May 2008
-
(2008)
IEEE Trans. Signal Process
, vol.56
, Issue.5
, pp. 1865-1877
-
-
Cattivelli, F.S.1
Lopes, C.G.2
Sayed, A.H.3
-
38
-
-
84863965241
-
Diffusion sparse least-mean squares over networks
-
Aug
-
Y. Liu, C. Li, and Z. Zhang, "Diffusion sparse least-mean squares over networks IEEE Trans. Signal Process., vol. 60, no. 8, pp. 4480-4485, Aug. 2012
-
(2012)
IEEE Trans. Signal Process
, vol.60
, Issue.8
, pp. 4480-4485
-
-
Liu, Y.1
Li, C.2
Zhang, Z.3
-
39
-
-
84900656099
-
Distributed sparse recursive least-squares over networks
-
Jun
-
Z. Liu, Y. Liu, and C. Li, "Distributed sparse recursive least-squares over networks IEEE Trans. Signal Process., vol. 62, no. 6, pp. 1386-1395, Jun. 2014
-
(2014)
IEEE Trans. Signal Process
, vol.62
, Issue.6
, pp. 1386-1395
-
-
Liu, Z.1
Liu, Y.2
Li, C.3
-
40
-
-
77953526250
-
Consensus-based distributed support vector machines
-
P. A. Forero, A. Cano, and G. B. Giannakis, "Consensus-based distributed support vector machines J. Mach. Learn. Res., vol. 11, pp. 1663-1707, 2010
-
(2010)
J. Mach. Learn. Res
, vol.11
, pp. 1663-1707
-
-
Forero, P.A.1
Cano, A.2
Giannakis, G.B.3
-
41
-
-
79960917469
-
Laplacian regularized Gaussian mixture model for data clustering
-
X. He, D. Cai, Y. Shao, H. Bao, and J. Han, "Laplacian regularized Gaussian mixture model for data clustering IEEE Trans. Knowl. Data Eng., vol. 23, no. 9, pp. 1406-1418, 2011
-
IEEE Trans. Knowl. Data Eng
, vol.23
, Issue.9
, pp. 1406-1418
-
-
He, X.1
Cai, D.2
Shao, Y.3
Bao, H.4
Han, J.5
-
42
-
-
33646557981
-
Optimizing the Cauchy-Schwarz PDF distance for information theoretic, non-parametric clustering
-
LNCS DOI 10.1007/11585978-3, Energy Minimization Methods in Computer Vision and Pattern Recognition - 5th International Workshop, EMMCVPR 2005, Proceedings
-
R. Jenssen, D. Erdogmus, K. E. Hild, J. C. Principe, and T. Eltoft, "Optimizing the Cauchy-Schwarz PDF divergence for information theoretic, non-parametric clustering in Proc. Int. Workshop on Energy Minimiz. Methods in Compute. Vision Pattern Recogn., St. Augustine, FL, USA, Nov. 2005, pp. 34-45. (Pubitemid 43722924
-
(2005)
Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics
, vol.3757
, pp. 34-45
-
-
Jenssen, R.1
Erdogmus, D.2
Hild, K.E.3
Principe, J.C.4
Eltoft, T.5
-
43
-
-
70349319868
-
Approximate distributed k-means clustering over a peer-To-peer network
-
Oct
-
S. Datta, C. R. Giannella, and H. Kargupta, "Approximate distributed k-means clustering over a peer-To-peer network IEEE Trans. Knowl. Data Eng., vol. 21, no. 10, pp. 1372-1388, Oct. 2009
-
(2009)
IEEE Trans. Knowl. Data Eng
, vol.21
, Issue.10
, pp. 1372-1388
-
-
Datta, S.1
Giannella, C.R.2
Kargupta, H.3
|