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Volumn , Issue , 2006, Pages 553-560

Stratification Learning: Detecting Mixed Density and Dimensionality in High Dimensional Point Clouds

Author keywords

[No Author keywords available]

Indexed keywords

HIGH-DIMENSIONAL; HIGHER-DIMENSIONAL; MANIFOLD LEARNING; MAXIMUM-LIKELIHOOD ESTIMATION; MIXTURE MODELING; POINT CLOUD DATA; POINT-CLOUDS; POISSON MIXTURES; REAL EXAMPLE; SOFT CLUSTERING;

EID: 85158056195     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (12)

References (17)
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    • Geodesic entropic graphs for dimension and entropy estimation in manifold learning
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    • Minimum effective dimension for mixtures of subspaces: A robust GPCA algorithm and its applications
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    • Huang, K.1    Ma, Y.2    Vidal, R.3
  • 9
    • 85156237082 scopus 로고    scopus 로고
    • Intrinsic dimension estimation using packing numbers
    • B. Kegl. Intrinsic dimension estimation using packing numbers. In Advances in NIPS 14, 2002.
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    • Kegl, B.1
  • 10
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    • Levina, E.1    Bickel, P.J.2
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    • Unsupervised dimensionality estimation and manifold learning in high-dimensional spaces by tensor voting
    • P. Mordohai and G. Medioni. Unsupervised dimensionality estimation and manifold learning in high-dimensional spaces by tensor voting. In IJCAI, page 798, 2005.
    • (2005) IJCAI , pp. 798
    • Mordohai, P.1    Medioni, G.2
  • 12
    • 0034704222 scopus 로고    scopus 로고
    • Nonlinear dimensionality reduction by locally linear embedding
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  • 14
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    • Manifold clustering
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.