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Volumn 4985 LNCS, Issue PART 2, 2008, Pages 683-692

Manifold construction by local neighborhood preservation

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATION COSTS; DATA POINTS; EUCLIDEAN DISTANCES; LINEAR ALGORITHMS;

EID: 54049103300     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-69162-4_71     Document Type: Conference Paper
Times cited : (40)

References (20)
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    • Conformality in the Self-Organization Network
    • Liou, C.Y., Tai, W.P.: Conformality in the Self-Organization Network. Artificial Intelligence 116, 265-286 (2000)
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  • 10
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    • Nonlinear Dimensionality Reduction by Locally Linear Embedding
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    • Think Globally, Fit Locally: Unsupervised Learning of Low Dimensional Manifolds
    • Saul, L., Roweis, S.: Think Globally, Fit Locally: Unsupervised Learning of Low Dimensional Manifolds. Journal of Machine Learning Research 4, 119-155 (2003)
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    • Saul, L.1    Roweis, S.2
  • 13
    • 84898986732 scopus 로고    scopus 로고
    • Jordan, M, Kearns, M, Solla, S, eds, pp, MIT Press, Cambridge
    • Tenenbaum, J.: Advances in Neural Information Processing 10. In: Jordan, M., Kearns, M., Solla, S. (eds.), pp. 682-688. MIT Press, Cambridge (1998)
    • (1998) Advances in Neural Information Processing , vol.10 , pp. 682-688
    • Tenenbaum, J.1
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    • 0034704229 scopus 로고    scopus 로고
    • A Global Geometric Framework for Non-linear Dimensionality Reduction
    • Tenenbaum, J., Silva, V., Langford, J.C.: A Global Geometric Framework for Non-linear Dimensionality Reduction. Science 290, 2319-2323 (2000)
    • (2000) Science , vol.290 , pp. 2319-2323
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.