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Volumn , Issue , 2003, Pages 479-484

Data clustering: Principal components, Hopfield and self-aggregation networks

Author keywords

[No Author keywords available]

Indexed keywords

COHERENT FRAMEWORKS; CONNECTION WEIGHTS; DATA CLUSTERING; HOPFIELD NETWORKS; OBJECTIVE FUNCTIONS; PRINCIPAL COMPONENTS; SELF AGGREGATION;

EID: 84864032147     PISSN: 10450823     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (2)

References (24)
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    • A spectral method to separate disconnected and nearly-disconnected web graph components
    • C. Ding, X. He, and H. Zha. A spectral method to separate disconnected and nearly-disconnected web graph components. In Proc. ACM Int'l Conf Knowledge Disc. Data Mining (KDD), pages 275-280,2001.
    • (2001) Proc. ACM Int'l Conf Knowledge Disc. Data Mining (KDD) , pp. 275-280
    • Ding, C.1    He, X.2    Zha, H.3
  • 8
    • 84880800658 scopus 로고    scopus 로고
    • Document retrieval and clustering: From principal component analysis to self-aggregation networks
    • C. Ding. Document retrieval and clustering: from principal component analysis to self-aggregation networks. Int'l Workshop onAl and Statistics, pages 78-85,2003.
    • (2003) Int'l Workshop onAl and Statistics , pp. 78-85
    • Ding, C.1
  • 9
    • 0001350119 scopus 로고
    • Algebraic connectivity of graphs
    • M. Fiedler. Algebraic connectivity of graphs. Czech. Math. J., 23:298-305,1973.
    • (1973) Czech. Math. J. , vol.23 , pp. 298-305
    • Fiedler, M.1
  • 11
    • 0026925324 scopus 로고
    • New spectral methods for ratio cut partitioning and clustering
    • L. Hagen and A.B. Kahng. New spectral methods for ratio cut partitioning and clustering. IEEE. Trans, on Computed Aided Desgin, 11:1074-1085,1992.
    • (1992) IEEE. Trans, on Computed Aided Desgin , vol.11 , pp. 1074-1085
    • Hagen, L.1    Kahng, A.B.2
  • 14
    • 0020118274 scopus 로고
    • Neural networks and physical systems with emergent collective computation abilities
    • J.J. Hopfield. Neural networks and physical systems with emergent collective computation abilities. Proc. Nat'l AcadSci USA, 79:2554-2558,1982.
    • (1982) Proc. Nat'l AcadSci USA , vol.79 , pp. 2554-2558
    • Hopfield, J.J.1
  • 16
    • 0026113980 scopus 로고
    • Nonlinear principal component analysis using autoassociativc neural networks
    • M. A. Kramer. Nonlinear principal component analysis using autoassociativc neural networks. AIChE Journal, 37:233-243,1991.
    • (1991) AIChE Journal , vol.37 , pp. 233-243
    • Kramer, M.A.1
  • 17
    • 0033592606 scopus 로고    scopus 로고
    • Learning the parts of objects with nonnegative matrix factorization
    • D. D. Lee and H. S. Seung. Learning the parts of objects with nonnegative matrix factorization. Nature, 401:788-791,1999.
    • (1999) Nature , vol.401 , pp. 788-791
    • Lee, D.D.1    Seung, H.S.2
  • 22
    • 0347243182 scopus 로고    scopus 로고
    • Nonlinear Component Analysis as a Kernel Eigenvalue Problem
    • B. Scholkopf, A. Smola, and K. Muller. Nonlinear component analysis as a kernel eigenvalue problem. Neural Computation, 10:1299-1319,1998. (Pubitemid 128463674)
    • (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.