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Volumn , Issue , 2008, Pages 139-146

Generating hypotheses of trends in high-dimensional data skeletons

Author keywords

G.4.1 mathematics of computing : mathematical software algorithm design and analysis; I.5.3 computing methodologies : pattern recognition clustering

Indexed keywords

ALGORITHM DESIGN AND ANALYSIS; COMPUTING METHODOLOGIES; CONTINUOUS SUPPORT; DATA SETS; EXPLORATORY DATA ANALYSIS; HIGH DIMENSIONAL DATA; MATHEMATICAL SOFTWARE; OPTIMAL PATHS; PRINCIPAL CURVE;

EID: 72749091674     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/VAST.2008.4677367     Document Type: Conference Paper
Times cited : (7)

References (13)
  • 2
    • 0042378381 scopus 로고    scopus 로고
    • Laplacian eigenmaps for dimensionality reduction and data representation
    • M. Belkin and P. Niyogi. Laplacian eigenmaps for dimensionality reduction and data representation. Neural Computation, 15(6):1373-1396, 2003.
    • (2003) Neural Computation , vol.15 , Issue.6 , pp. 1373-1396
    • Belkin, M.1    Niyogi, P.2
  • 5
    • 0037948870 scopus 로고    scopus 로고
    • Hessian eigenmaps: Locally linear embedding techniques for high-dimensional data
    • D. L. Donoho and C. Grimes. Hessian eigenmaps: Locally linear embedding techniques for high-dimensional data. Proceedings of the National Academy of Sciences, 100(10):5591-5596, 2003.
    • (2003) Proceedings of the National Academy of Sciences , vol.100 , Issue.10 , pp. 5591-5596
    • Donoho, D.L.1    Grimes, C.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.