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Volumn , Issue , 2013, Pages

Discriminative k-means clustering

Author keywords

[No Author keywords available]

Indexed keywords

CLUSTER STRUCTURE; K-MEANS; K-MEANS ALGORITHM; K-MEANS CLUSTERING; LARGE PARTS; PARTITIONAL CLUSTERING;

EID: 84893550189     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IJCNN.2013.6707038     Document Type: Conference Paper
Times cited : (10)

References (23)
  • 2
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    • Cluster analysis of massive datasets in astronomy
    • W. Jang and M. Hendry, "Cluster analysis of massive datasets in astronomy." Journal of Statistics and Computing, vol. 17, no. 3, pp. 253-262, 2007.
    • (2007) Journal of Statistics and Computing , vol.17 , Issue.3 , pp. 253-262
    • Jang, W.1    Hendry, M.2
  • 3
    • 3042535216 scopus 로고    scopus 로고
    • Distinctive image features from scaleinvariant keypoints
    • D. G. Lowe, "Distinctive image features from scaleinvariant keypoints." International Journal of Computer Vision, vol. 60, no. 2, pp. 91-110, 2003.
    • (2003) International Journal of Computer Vision , vol.60 , Issue.2 , pp. 91-110
    • Lowe, D.G.1
  • 11
    • 84893606244 scopus 로고    scopus 로고
    • Learning atomic human actions using variablelength markov models
    • (to appear)
    • C. Liang, "Learning atomic human actions using variablelength Markov models." IEEE Transactions on Multimedia, 2013, (to appear).
    • (2013) IEEE Transactions on Multimedia
    • Liang, C.1
  • 14
    • 72149085374 scopus 로고    scopus 로고
    • How many clusters?
    • P. McCullagh and J. Yang, "How many clusters?" Bayesian Analysis, vol. 3, no. 1, pp. 101-120, 2008.
    • (2008) Bayesian Analysis , vol.3 , Issue.1 , pp. 101-120
    • McCullagh, P.1    Yang, J.2
  • 17
    • 77950369345 scopus 로고    scopus 로고
    • Data clustering: 50 years beyond kmeans
    • A. K. Jain, "Data clustering: 50 years beyond kmeans." Pattern Recognition Letters, vol. 31, no. 8, pp. 651-666, 2010.
    • (2010) Pattern Recognition Letters , vol.31 , Issue.8 , pp. 651-666
    • Jain, A.K.1
  • 19
    • 0033204902 scopus 로고    scopus 로고
    • An empirical comparison of four initialization methods for the kmeans algorithm
    • J. M. Pena, J. A. Lozano, and P. Larranaga, "An empirical comparison of four initialization methods for the kmeans algorithm." Pattern Recognition Letters, vol. 20, no. 10, pp. 1027-1040, 1999.
    • (1999) Pattern Recognition Letters , vol.20 , Issue.10 , pp. 1027-1040
    • Pena, J.M.1    Lozano, J.A.2    Larranaga, P.3
  • 20
    • 23844528211 scopus 로고    scopus 로고
    • Cluster center initialization algorithm for kmeans clustering
    • S. S. Khan and A. Ahmadb, "Cluster center initialization algorithm for kmeans clustering." Pattern Recognition Letters, vol. 25, no. 11, pp. 1293-1302, 2004.
    • (2004) Pattern Recognition Letters , vol.25 , Issue.11 , pp. 1293-1302
    • Khan, S.S.1    Ahmadb, A.2
  • 21
    • 0015644825 scopus 로고
    • A fuzzy relative of the isodata process and its use in detecting compact wellseparated clusters
    • J. C. Dunn, "A fuzzy relative of the ISODATA process and its use in detecting compact wellseparated clusters." Journal of Cybernetics, vol. 3, pp. 32-57, 1973.
    • (1973) Journal of Cybernetics , vol.3 , pp. 32-57
    • Dunn, J.C.1
  • 23
    • 0347243182 scopus 로고    scopus 로고
    • Nonlinear component analysis as a kernel eigenvalue problem
    • B. Scholkopf, A. Smola, and K.R. Muller, "Nonlinear component analysis as a kernel eigenvalue problem." Neural Computation, vol. 10, no. 5, pp. 1299-1319, 1998.
    • (1998) Neural Computation , vol.10 , Issue.5 , pp. 1299-1319
    • Scholkopf, B.1    Smola, A.2    Muller, K.R.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.