-
1
-
-
33748060966
-
How slow is the k-means method?
-
D. Arthur and S. Vassilvitskii. How slow is the k-means method? In SoCG, pages 144-153, 2006.
-
(2006)
SoCG
, pp. 144-153
-
-
Arthur, D.1
Vassilvitskii, S.2
-
2
-
-
85153959666
-
Convergence properties of the K-means algorithms
-
L. Bottou and Y. Bengio. Convergence properties of the K-means algorithms. In NIPS, pages 585-592, 1995.
-
(1995)
In NIPS
, pp. 585-592
-
-
Bottou, L.1
Bengio, Y.2
-
3
-
-
0002550769
-
Refining initial points for K-Means clustering
-
P S. Bradley and U. M. Fayyad. Refining initial points for K-Means clustering. In ICML, pages 91-99, 1998.
-
(1998)
ICML
, pp. 91-99
-
-
Bradley, P.S.1
Fayyad, U.M.2
-
5
-
-
14344257496
-
K-means clustering via principal component analysis
-
C. H. Q. Ding and X. He. K-means clustering via principal component analysis. In ICML, 2004.
-
(2004)
ICML
-
-
Ding, C.H.Q.1
He, X.2
-
6
-
-
1942485278
-
Using the triangle inequality to accelerate k-means
-
C. Elkan. Using the triangle inequality to accelerate k-means. In ICML, pages 147-153, 2003.
-
(2003)
ICML
, pp. 147-153
-
-
Elkan, C.1
-
8
-
-
20744439992
-
How fast is the k-means method?
-
S. Har-Peled and B. Sadri. How fast is the k-means method? In SODA, pages 877-885, 2005.
-
(2005)
SODA
, pp. 877-885
-
-
Har-Peled, S.1
Sadri, B.2
-
9
-
-
0027928863
-
Applications of weighted voronoi diagrams and randomization to variance-based - clustering (extended abstract)
-
M. Inaba, N. Katoh, and H. Imai. Applications of weighted voronoi diagrams and randomization to variance-based - clustering (extended abstract). In Symposium on Computational Geometry, pages 332-339, 1994.
-
(1994)
Symposium on Computational Geometry
, pp. 332-339
-
-
Inaba, M.1
Katoh, N.2
Imai, H.3
-
10
-
-
34748894654
-
-
T. Kanungo, D. Mount, N. Netanyahu, C. Piatko, R. Silverman, and A. Wu. An efficient k-means clustering algorithm: analysis and implementation, 2002.
-
(2002)
An efficient k-means clustering algorithm: Analysis and implementation
-
-
Kanungo, T.1
Mount, D.2
Netanyahu, N.3
Piatko, C.4
Silverman, R.5
Wu, A.6
-
11
-
-
2442683961
-
A local search approximation algorithm for k-means clustering
-
T. Kanungo, D. M. Mount, N. S. Netanyahu, C. D. Piatko, R. Silverman, and A. Y. Wu. A local search approximation algorithm for k-means clustering. Comput. Geom., 28(2-3):89-112, 2004.
-
(2004)
Comput. Geom
, vol.28
, Issue.2-3
, pp. 89-112
-
-
Kanungo, T.1
Mount, D.M.2
Netanyahu, N.S.3
Piatko, C.D.4
Silverman, R.5
Wu, A.Y.6
-
12
-
-
11244288693
-
A simple linear time (1+ε)-approximation algorithm for k-means clustering in any dimensions
-
A. Kumar, Y. Sabharwal, and S. Sen. A simple linear time (1+ε)-approximation algorithm for k-means clustering in any dimensions. In FOCS, pages 454-462, 2004.
-
(2004)
FOCS
, pp. 454-462
-
-
Kumar, A.1
Sabharwal, Y.2
Sen, S.3
-
15
-
-
0002738562
-
Accelerating exact k -means algorithms with geometric reasoning
-
D. Pelleg and A. Moore. Accelerating exact k -means algorithms with geometric reasoning. In Knowledge Discovery and Data Mining, pages 277-281, 1999.
-
(1999)
Knowledge Discovery and Data Mining
, pp. 277-281
-
-
Pelleg, D.1
Moore, A.2
-
16
-
-
0030157145
-
BIRCH: An efficient data clustering method for very large databases
-
T. Zhang, R. Ramakrishnan, and M. Livny. BIRCH: an efficient data clustering method for very large databases. In SIGMOD Conference, pages 103-114, 1996.
-
(1996)
SIGMOD Conference
, pp. 103-114
-
-
Zhang, T.1
Ramakrishnan, R.2
Livny, M.3
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