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Volumn 2, Issue , 2012, Pages 1079-1087

Clustering by Nonnegative Matrix Factorization using graph randomwalk

Author keywords

[No Author keywords available]

Indexed keywords

LEAST SQUARE ERRORS; MINIMIZATION ALGORITHMS; MULTIPLICATIVE MAJORIZATION; NONNEGATIVE MATRIX FACTORIZATION; OBJECTIVE FUNCTIONS; REAL-WORLD DATASETS; RELAXATION TECHNIQUES; SCALABLE IMPLEMENTATION;

EID: 84877757238     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (71)

References (29)
  • 1
    • 84877752527 scopus 로고    scopus 로고
    • http://users.ics.aalto.fi/rozyang/nmfr/index.shtml.
  • 2
    • 80053457289 scopus 로고    scopus 로고
    • Clustering by left-stochastic matrix factorization
    • R. Arora, M. Gupta, A. Kapila, and M. Fazel. Clustering by left-stochastic matrix factorization. In ICML, 2011.
    • (2011) ICML
    • Arora, R.1    Gupta, M.2    Kapila, A.3    Fazel, M.4
  • 5
    • 79960337319 scopus 로고    scopus 로고
    • Generalized alpha-beta divergences and their application to robust nonnegative matrix factorization
    • A. Cichocki, S. Cruces, and S. Amari. Generalized alpha-beta divergences and their application to robust nonnegative matrix factorization. Entropy, 13:134-170, 2011.
    • (2011) Entropy , vol.13 , pp. 134-170
    • Cichocki, A.1    Cruces, S.2    Amari, S.3
  • 6
    • 12244256379 scopus 로고    scopus 로고
    • Kernel k-means, spectral clustering and normalized cuts
    • I. Dhillon, Y. Guan, and B. Kulis. Kernel k-means, spectral clustering and normalized cuts. In KDD, 2004.
    • (2004) KDD
    • Dhillon, I.1    Guan, Y.2    Kulis, B.3
  • 7
    • 33749255098 scopus 로고    scopus 로고
    • On the equivalence of nonnegative matrix factorization and spectral clustering
    • C. Ding, X. He, and H. D. Simon. On the equivalence of nonnegative matrix factorization and spectral clustering. In ICDM, 2005.
    • (2005) ICDM
    • Ding, C.1    He, X.2    Simon, H.D.3
  • 8
    • 67049146331 scopus 로고    scopus 로고
    • Nonnegative matrix factorization for combinatorial optimization: Spectral clustering, graph matching, and clique finding
    • C. Ding, T. Li, and M. I. Jordan. Nonnegative matrix factorization for combinatorial optimization: Spectral clustering, graph matching, and clique finding. In ICDM, 2008.
    • (2008) ICDM
    • Ding, C.1    Li, T.2    Jordan, M.I.3
  • 10
    • 41249089920 scopus 로고    scopus 로고
    • On the equivalence between non-negative matrix factorization and probabilistic laten semantic indexing
    • C. Ding, T. Li, and W. Peng. On the equivalence between non-negative matrix factorization and probabilistic laten semantic indexing. Computational Statistics and Data Analysis, 52(8):3913-3927, 2008.
    • (2008) Computational Statistics and Data Analysis , vol.52 , Issue.8 , pp. 3913-3927
    • Ding, C.1    Li, T.2    Peng, W.3
  • 11
    • 33749575326 scopus 로고    scopus 로고
    • Orthogonal nonnegative matrix t-factorizations for clustering
    • C. Ding, T. Li, W. Peng, and H. Park. Orthogonal nonnegative matrix t-factorizations for clustering. In SIGKDD, 2006.
    • (2006) SIGKDD
    • Ding, C.1    Li, T.2    Peng, W.3    Park, H.4
  • 12
    • 85162319688 scopus 로고    scopus 로고
    • Sparse manifold clustering and embedding
    • E. Elhamifar and R. Vidal. Sparse manifold clustering and embedding. In NIPS, 2011.
    • (2011) NIPS
    • Elhamifar, E.1    Vidal, R.2
  • 13
    • 83855161608 scopus 로고    scopus 로고
    • Symmetric nonnegative matrix factorization: Algorithms and applications to probabilistic clustering
    • Z. He, S. Xie, R. Zdunek, G. Zhou, and A. Cichocki. Symmetric nonnegative matrix factorization: Algorithms and applications to probabilistic clustering. IEEE Transactions on Neural Networks, 22(12):2117-2131, 2011.
    • (2011) IEEE Transactions on Neural Networks , vol.22 , Issue.12 , pp. 2117-2131
    • He, Z.1    Xie, S.2    Zdunek, R.3    Zhou, G.4    Cichocki, A.5
  • 14
    • 85162008147 scopus 로고    scopus 로고
    • An inverse power method for nonlinear eigenproblems with applications in 1-Spectral clustering and sparse PCA
    • M. Hein and T. Bühler. An inverse power method for nonlinear eigenproblems with applications in 1-Spectral clustering and sparse PCA. In NIPS, 2010.
    • (2010) NIPS
    • Hein, M.1    Bühler, T.2
  • 15
    • 0001093042 scopus 로고    scopus 로고
    • Algorithms for non-negative matrix factorization
    • D. D. Lee and H. S. Seung. Algorithms for non-negative matrix factorization. In NIPS, 2000.
    • (2000) NIPS
    • Lee, D.D.1    Seung, H.S.2
  • 16
    • 35548969471 scopus 로고    scopus 로고
    • Projected gradient methods for non-negative matrix factorization
    • C.-J. Lin. Projected gradient methods for non-negative matrix factorization. Neural Computation, 19:2756-2779, 2007.
    • (2007) Neural Computation , vol.19 , pp. 2756-2779
    • Lin, C.-J.1
  • 17
    • 84996143328 scopus 로고    scopus 로고
    • How the result of graph clustering methods depends on the construction of the graph
    • in press
    • M. Maier, U. von Luxburg, and M. Hein. How the result of graph clustering methods depends on the construction of the graph. ESAIM: Probability & Statistics, 2012. in press.
    • (2012) ESAIM: Probability & Statistics
    • Maier, M.1    Von Luxburg, U.2    Hein, M.3
  • 20
    • 0041875229 scopus 로고    scopus 로고
    • On spectral clustering: Analysis and an algorithm
    • A. Ng, M. Jordan, and Y. Weiss. On spectral clustering: Analysis and an algorithm. In NIPS, 2001.
    • (2001) NIPS
    • Ng, A.1    Jordan, M.2    Weiss, Y.3
  • 23
    • 77951938107 scopus 로고    scopus 로고
    • Linear and nonlinear projective nonnegative matrix factorization
    • Z. Yang and E. Oja. 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
  • 24
    • 83855163513 scopus 로고    scopus 로고
    • Unified development of multiplicative algorithms for linear and quadratic nonnegative matrix factorization
    • Z. Yang and E. Oja. 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
  • 25
    • 84867135689 scopus 로고    scopus 로고
    • Clustering by low-rank doubly stochastic matrix decomposition
    • Z. Yang and E. Oja. Clustering by low-rank doubly stochastic matrix decomposition. In ICML, 2012.
    • (2012) ICML
    • Yang, Z.1    Oja, E.2
  • 26
    • 83655184772 scopus 로고    scopus 로고
    • Quadratic nonnegative matrix factorization
    • Z. Yang and E. Oja. Quadratic nonnegative matrix factorization. Pattern Recognition, 45(4):1500-1510, 2012.
    • (2012) Pattern Recognition , vol.45 , Issue.4 , pp. 1500-1510
    • Yang, Z.1    Oja, E.2
  • 27
    • 33745936031 scopus 로고    scopus 로고
    • A unifying approach to hard and probabilistic clustering
    • R. Zass and A. Shashua. A unifying approach to hard and probabilistic clustering. In ICCV, 2005.
    • (2005) ICCV
    • Zass, R.1    Shashua, A.2
  • 28
    • 33644783522 scopus 로고    scopus 로고
    • Self-tuning spectral clustering
    • L. Zelnik-Manor and P. Perona. Self-tuning spectral clustering. In NIPS, 2004.
    • (2004) NIPS
    • Zelnik-Manor, L.1    Perona, P.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.