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Volumn 6594 LNCS, Issue PART 2, 2011, Pages 295-304

About nonnegative matrix factorization: On the posrank approximation

Author keywords

dimensionality reduction; feature extraction; non negative matrix factorization; Signal processing

Indexed keywords

DIMENSIONALITY REDUCTION; GLOBAL OPTIMIZATION TECHNIQUES; LOCAL MINIMUMS; NON NEGATIVE MATRIX FACTORIZATION; NON-LINEAR OPTIMIZATION PROBLEMS;

EID: 79955095098     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-20267-4_31     Document Type: Conference Paper
Times cited : (2)

References (12)
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    • Higham, N.J.1
  • 5
    • 35548969471 scopus 로고    scopus 로고
    • Projected Gradient Methods for Non-negative Matrix Factorization
    • Lin, C.: Projected Gradient Methods for Non-negative Matrix Factorization. Neural Computing 19, 2756-2779 (2007)
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    • Lee, D.D., Seung, H.S.: Algorithms for nonnegative matrix factorization. In: Advances in Neural Information Processing, vol. 13, pp. 556-562. MIT Press, Cambridge (2001)
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    • Hoyer, P.O.: Nonnegative Matrix Factorization with Sparseness Constraits. Journal of Machine Learning Research 5, 1457-1469 (2004)
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  • 9
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    • Positive Matrix Factorization: A non-negative factor model with optimal utilization of error estimates of data values
    • Paatero, P., Tapper, U.: Positive Matrix Factorization: a non-negative factor model with optimal utilization of error estimates of data values. Environmetrics 5, 111-126 (1994)
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.