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Volumn 5629 LNCS, Issue , 2009, Pages 344-352

The exploration machine - A novel method for data visualization

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONALLY EFFICIENT; DATA CLUSTERING; DIFFERENT DOMAINS; DIMENSIONALITY REDUCTION; GRAPHICAL REPRESENTATIONS; HIGH-DIMENSIONAL; MACHINE-LEARNING; MODEL ADAPTATION; NOVEL METHODS; SCIENTIFIC DATA; SELF-ORGANIZED; STRUCTURE-PRESERVING;

EID: 69049109914     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-02397-2_39     Document Type: Conference Paper
Times cited : (68)

References (10)
  • 3
    • 0344972928 scopus 로고    scopus 로고
    • Self-organizing maps: Generalizations and new optimization techniques
    • Graepel, T., Burger, M., Obermayer, K.: Self-organizing maps: Generalizations and new optimization techniques. Neurocomputing 21, 173-190 (1998)
    • (1998) Neurocomputing , vol.21 , pp. 173-190
    • Graepel, T.1    Burger, M.2    Obermayer, K.3
  • 5
    • 0034704222 scopus 로고    scopus 로고
    • Nonlinear dimensionality reduction by locally linear embedding
    • Roweis, S.T., Saul, L.K.: Nonlinear dimensionality reduction by locally linear embedding. Science 290(5500), 2323-2326 (2000)
    • (2000) Science , vol.290 , Issue.5500 , pp. 2323-2326
    • Roweis, S.T.1    Saul, L.K.2
  • 6
    • 84887006810 scopus 로고
    • A nonlinear mapping for data structure analysis
    • Sammon, J.W.: A nonlinear mapping for data structure analysis. IEEE Transactions on Computers C 18, 401-409 (1969)
    • (1969) IEEE Transactions on Computers C , vol.18 , pp. 401-409
    • Sammon, J.W.1
  • 7
    • 0034704229 scopus 로고    scopus 로고
    • A global geometric framework for nonlinear dimensionality reduction
    • Tenenbaum, J.B., de Silva, V., Langford, C.: A global geometric framework for nonlinear dimensionality reduction. Science 290(5500), 2319-2323 (2000)
    • (2000) Science , vol.290 , Issue.5500 , pp. 2319-2323
    • Tenenbaum, J.B.1    de Silva, V.2    Langford, C.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.