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Volumn 6365 LNCS, Issue , 2010, Pages 514-521

Automatic rank determination in projective nonnegative matrix factorization

Author keywords

[No Author keywords available]

Indexed keywords

AUTOMATIC RELEVANCE DETERMINATION; CLUSTERING APPLICATIONS; COLUMN RANKS; DATA SETS; EXPECTATION MAXIMIZATION; MULTIPLICATIVE UPDATES; NUMBER OF CLUSTERS; PROJECTION MATRIX; PROJECTIVE NONNEGATIVE MATRIX FACTORIZATION; REAL-WORLD DATASETS;

EID: 78349303501     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-15995-4_64     Document Type: Conference Paper
Times cited : (13)

References (15)
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    • Learning the parts of objects by non-negative matrix factorization
    • Lee, D.D., Seung, H.S.: Learning the parts of objects by non-negative matrix factorization. Nature 401, 788-791 (1999)
    • (1999) Nature , vol.401 , pp. 788-791
    • Lee, D.D.1    Seung, H.S.2
  • 3
  • 6
    • 26444591944 scopus 로고    scopus 로고
    • Projective nonnegative matrix factorization for image compression and feature extraction
    • Kalviainen, H., Parkkinen, J., Kaarna, A. (eds.) SCIA 2005. Springer, Heidelberg
    • Yuan, Z., Oja, E.: Projective nonnegative matrix factorization for image compression and feature extraction. In: Kalviainen, H., Parkkinen, J., Kaarna, A. (eds.) SCIA 2005. LNCS, vol. 3540, pp. 333-342. Springer, Heidelberg (2005)
    • (2005) LNCS , vol.3540 , pp. 333-342
    • Yuan, Z.1    Oja, E.2
  • 8
    • 77951938107 scopus 로고    scopus 로고
    • Linear and nonlinear projective nonnegative matrix factorization
    • Yang, Z., 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
  • 9
    • 0001441372 scopus 로고
    • Probable networks and plausible predictions - A review of practical bayesian methods for supervised neural networks
    • Mackay, D.J.C.: Probable networks and plausible predictions - a review of practical bayesian methods for supervised neural networks. Network: Computation in Neural Systems 6(3), 469-505 (1995)
    • (1995) Network: Computation in Neural Systems , vol.6 , Issue.3 , pp. 469-505
    • Mackay, D.J.C.1
  • 11
    • 0001224048 scopus 로고    scopus 로고
    • Sparse bayesian learning and the relevance vector machine
    • Tipping, M.E.: Sparse bayesian learning and the relevance vector machine. Journal of Machine Learning Research 1, 211-244 (2001)
    • (2001) Journal of Machine Learning Research , vol.1 , pp. 211-244
    • Tipping, M.E.1
  • 14
    • 23744456750 scopus 로고    scopus 로고
    • When does non-negative matrix factorization give a correct decomposition into parts?
    • Donoho, D., Stodden, V.: When does non-negative matrix factorization give a correct decomposition into parts? Advances in Neural Information Processing Systems 16, 1141-1148 (2003)
    • (2003) Advances in Neural Information Processing Systems , vol.16 , pp. 1141-1148
    • Donoho, D.1    Stodden, V.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.