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Volumn , Issue , 2009, Pages 1923-1927

Tuning pruning in sparse non-negative matrix factorization

Author keywords

[No Author keywords available]

Indexed keywords

AUTOMATIC RELEVANCE DETERMINATION; BAYESIAN MODELLING; EXPLORATORY ANALYSIS; HIERARCHICAL BAYESIAN; INTERPRETABLE REPRESENTATION; MODEL ORDER; NONNEGATIVE MATRIX FACTORIZATION; NONUNIQUENESS; NUMBER OF COMPONENTS; SPARSE NON-NEGATIVE MATRIX FACTORIZATIONS;

EID: 84863731295     PISSN: 22195491     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (34)

References (30)
  • 1
    • 0016355478 scopus 로고
    • A new look at the statistical model identification
    • IEEE Transactions on
    • H. Akaike. A new look at the statistical model identification. Automatic Control, IEEE Transactions on, 19(6):716-723, 1974.
    • (1974) Automatic Control , vol.19 , Issue.6 , pp. 716-723
    • Akaike, H.1
  • 3
    • 0642334046 scopus 로고    scopus 로고
    • A fast non-negativity-constrained least squares algorithm
    • R. Bro and S. de Jong. A fast non-negativity-constrained least squares algorithm. J. of Chemometrics, 11(5):393-401, 1997.
    • (1997) J. of Chemometrics , vol.11 , Issue.5 , pp. 393-401
    • Bro, R.1    De Jong, S.2
  • 4
    • 34547497161 scopus 로고    scopus 로고
    • Nonnegative tensor factorization using alpha and beta divergences
    • A. Cichocki, R. Zdunek, S. Choi, R. Plemmons, and S. Amari. Nonnegative tensor factorization using alpha and beta divergences. ICASSP, 2007.
    • (2007) ICASSP
    • Cichocki, A.1    Zdunek, R.2    Choi, S.3    Plemmons, R.4    Amari, S.5
  • 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. Proc. SIAM Internat. Conf. Data Min. (SDM'05), pages 606-610, 2005.
    • (2005) Proc. SIAM Internat. Conf. Data Min. (SDM'05) , pp. 606-610
    • Ding, C.1    He, X.2    Simon, H.D.3
  • 9
    • 23744456750 scopus 로고    scopus 로고
    • When does nonnegative matrix factorization give a correct decomposition into parts?
    • D. Donoho and V. Stodden. When does nonnegative matrix factorization give a correct decomposition into parts? In Advances in Neural Information Processing Systems 16, 2003.
    • (2003) Advances in Neural Information Processing Systems , vol.16
    • Donoho, D.1    Stodden, V.2
  • 10
    • 10944227316 scopus 로고    scopus 로고
    • Sparse coding and nmf
    • J. Eggert and E. Körner. Sparse coding and nmf. In Neural Networks, volume 4, pages 2529-2533, 2004.
    • (2004) Neural Networks , vol.4 , pp. 2529-2533
    • Eggert, J.1    Körner, E.2
  • 11
    • 84900510076 scopus 로고    scopus 로고
    • Non-negative matrix factorization with sparseness constraints
    • P. O. Hoyer. Non-negative matrix factorization with sparseness constraints. Journal of Machine Learning Research, 5:1457-1469, 2004.
    • (2004) Journal of Machine Learning Research , vol.5 , pp. 1457-1469
    • Hoyer, P.O.1
  • 12
    • 84857841726 scopus 로고    scopus 로고
    • Non-negative sparse coding
    • Proceedings of the 2002 12th IEEE Workshop on
    • P.O. Hoyer. Non-negative sparse coding. Neural Networks for Signal Processing, 2002. Proceedings of the 2002 12th IEEE Workshop on, pages 557-565, 2002.
    • (2002) Neural Networks for Signal Processing, 2002 , pp. 557-565
    • Hoyer, P.O.1
  • 13
    • 34250922831 scopus 로고
    • The varimax criterion for analytic rotation in factor analysis
    • H. F. Kaiser. The varimax criterion for analytic rotation in factor analysis. Psychometrica, 23:187-200, 1958.
    • (1958) Psychometrica , vol.23 , pp. 187-200
    • Kaiser, H.F.1
  • 14
    • 70350175761 scopus 로고    scopus 로고
    • Fast projection-based methods for the least squares nonnegative matrix approximation problem
    • D. Kim, S. Sra, and I. S. Dhillon. Fast projection-based methods for the least squares nonnegative matrix approximation problem. Stat. Anal. Data Min., 1(1):38-51, 2008.
    • (2008) Stat. Anal. Data Min. , vol.1 , Issue.1 , pp. 38-51
    • Kim, D.1    Sra, S.2    Dhillon, I.S.3
  • 16
    • 84863742165 scopus 로고
    • of Classics in Applied Mathematics. SIAM, Philadelphia, PA
    • C.L. Lawson and R.J. Hanson. Solving Least Squares Problems, volume 15 of Classics in Applied Mathematics. SIAM, Philadelphia, PA, 1995, 1974.
    • (1995) Solving Least Squares Problems , vol.15 , pp. 1974
    • Lawson, C.L.1    Hanson, R.J.2
  • 17
    • 0001093042 scopus 로고    scopus 로고
    • Algorithms for nonnegative matrix factorization
    • D. D. Lee and H. S. Seung. Algorithms for nonnegative matrix factorization. In NIPS, pages 556-562, 2000.
    • (2000) NIPS , pp. 556-562
    • Lee, D.D.1    Seung, H.S.2
  • 18
    • 0033592606 scopus 로고    scopus 로고
    • Learning the parts of objects by nonnegative matrix factorization
    • D.D. Lee and H.S. Seung. Learning the parts of objects by nonnegative matrix factorization. Nature, 401(6755):788-91, 1999.
    • (1999) Nature , vol.401 , Issue.6755 , pp. 788-791
    • Lee, D.D.1    Seung, H.S.2
  • 19
    • 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
  • 20
    • 0001025418 scopus 로고
    • Bayesian interpolation
    • D. J. C. Mackay. Bayesian interpolation. Neural Computation, 4:415-447, 1992.
    • (1992) Neural Computation , vol.4 , pp. 415-447
    • Mackay, D.J.C.1
  • 21
    • 33947514540 scopus 로고    scopus 로고
    • Erpwavelab a toolbox for multi-channel analysis of time-frequency transformed event related potentials
    • M. Mørup, L.K. Hansen, and S. M. Arnfred. Erpwavelab a toolbox for multi-channel analysis of time-frequency transformed event related potentials. Journal of Neuroscience Methods, 161(361-368), 2007.
    • (2007) Journal of Neuroscience Methods , vol.161 , pp. 361-368
    • Mørup, M.1    Hansen, L.K.2    Arnfred, S.M.3
  • 22
    • 48249100881 scopus 로고    scopus 로고
    • Algorithms for sparse non-negative tucker
    • M. Mørup, L.K. Hansen, and S. M. Arnfred. Algorithms for sparse non-negative tucker. Neural Computation, 20(8):2112-2131, 2008
    • (2008) Neural Computation , vol.20 , Issue.8 , pp. 2112-2131
    • Mørup, M.1    Hansen, L.K.2    Arnfred, S.M.3
  • 24
    • 84863774108 scopus 로고    scopus 로고
    • Automatic relevance determination for multi-way models
    • accepted for publication
    • M. Mørup and L. K. Hansen. Automatic relevance determination for multi-way models. accepted for publication, Journal of Chemometrics, 22:1-12, 2009.
    • (2009) Journal of Chemometrics , vol.22 , pp. 1-12
    • Mørup, M.1    Hansen, L.K.2
  • 25
    • 0028561099 scopus 로고
    • Positive matrix factorization: A nonnegative factor model with optimal utilization of error estimates of data values
    • P Paatero and U Tapper. Positive matrix factorization: A nonnegative factor model with optimal utilization of error estimates of data values. Environmetrics, 5(2):111-126, 1994.
    • (1994) Environmetrics , vol.5 , Issue.2 , pp. 111-126
    • Paatero, P.1    Tapper, U.2
  • 28
    • 84863494643 scopus 로고    scopus 로고
    • Bayesian non-negative matrix factorization
    • accepted for publication
    • M. N. Schmidt, O. Winther, and L. K. Hansen. Bayesian non-negative matrix factorization. accepted for publication ICA 2009.
    • ICA 2009
    • Schmidt, M.N.1    Winther, O.2    Hansen, L.K.3
  • 29
    • 0000120766 scopus 로고
    • Estimating the dimension of a model
    • G. Schwarz. Estimating the dimension of a model. Annals of Statistics, 6(2):461-464, 1978.
    • (1978) Annals of Statistics , vol.6 , Issue.2 , pp. 461-464
    • Schwarz, G.1


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