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Volumn 1, Issue , 2012, Pages 831-838

Clustering by low-rank doubly stochastic matrix decomposition

Author keywords

[No Author keywords available]

Indexed keywords

APPROXIMATION APPROACH; APPROXIMATION ERRORS; CLUSTERING ANALYSIS; DATA SETS; DIRICHLET PRIOR; DISCRIMINATIVE MODELS; DOUBLY STOCHASTIC MATRIX; KULLBACK LEIBLER DIVERGENCE; LEARNING METHODS; LOCAL MINIMUMS; LOW RANK APPROXIMATIONS; MATRIX FACTORIZATIONS; PROBABILISTIC INTERPRETATION; RANDOM WALK; VIRTUAL CLUSTERS;

EID: 84867135689     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (27)

References (17)
  • 5
    • 67049146331 scopus 로고    scopus 로고
    • Nonnegative matrix factorization for combinatorial optimization: Spectral clustering, graph matching, and clique finding
    • Ding, C., Li, T., and Jordan, M. I. Nonnegative matrix factorization for combinatorial optimization: Spectral clustering, graph matching, and clique finding. In International Conference on Data Mining (ICDM), pp. 183-192, 2008.
    • (2008) International Conference on Data Mining (ICDM) , pp. 183-192
    • Ding, C.1    Li, T.2    Jordan, M.I.3
  • 7
    • 85162008147 scopus 로고    scopus 로고
    • An inverse power method for nonlinear eigenproblems with applications in 1-spectral clustering and sparse pca
    • Hein, M. and Bühler, T. An inverse power method for nonlinear eigenproblems with applications in 1-spectral clustering and sparse pca. In Advances in Neural Information Processing Systems (NIPS), pp. 847-855, 2010.
    • (2010) Advances in Neural Information Processing Systems (NIPS) , pp. 847-855
    • Hein, M.1    Bühler, T.2
  • 15
    • 77951938107 scopus 로고    scopus 로고
    • Linear and nonlinear projective nonnegative matrix factorization
    • Yang, Z. and Oja, E. Linear and nonlinear projective nonnegative matrix factorization. IEEE Transaction on Neural Networks, 21(5):734-749, 2010.
    • (2010) IEEE Transaction on Neural Networks , vol.21 , Issue.5 , pp. 734-749
    • Yang, Z.1    Oja, E.2
  • 16
    • 83855163513 scopus 로고    scopus 로고
    • Unified development of multiplicative algorithms for linear and quadratic nonnegative matrix factorization
    • Yang, Z. and Oja, E. Unified development of multiplicative algorithms for linear and quadratic nonnegative matrix factorization. IEEE Transactions on Neural Networks, 22(12):1878-1891, 2011.
    • (2011) IEEE Transactions on Neural Networks , vol.22 , Issue.12 , pp. 1878-1891
    • Yang, Z.1    Oja, E.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.