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Volumn 1, Issue , 2011, Pages 501-506

Towards evolutionary nonnegative matrix factorization

Author keywords

[No Author keywords available]

Indexed keywords

DATA FEATURE; DATA MATRICES; INTERPRETABILITY; NONNEGATIVE MATRIX FACTORIZATION; REAL WORLD DATA; REAL-WORLD APPLICATION; SPACE EFFICIENT;

EID: 80055037014     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (18)

References (18)
  • 1
    • 0028990423 scopus 로고
    • Source identification of bulk wet deposition in Finland by positive matrix factorization
    • Anttila, P.; Paatero, P.; Tapper, U.; and Järvinen, O. 1995. Source identification of bulk wet deposition in finland by positive matrix factorization. Atmospheric Environment 29(14):1705-1718. (Pubitemid 26436827)
    • (1995) Atmospheric Environment , vol.29 , Issue.14 , pp. 1705-1718
    • Anttila, P.1    Paatero, P.2    Tapper, U.3    Jarvinen, O.4
  • 5
    • 84864031935 scopus 로고    scopus 로고
    • Generalized nonnegative matrix approximations with Bregman divergences
    • Dhillon, I. S., and Sra, S. 2005. Generalized nonnegative matrix approximations with Bregman divergences. In Advances in Neural Information Proc. Systems, 283-290.
    • (2005) Advances in Neural Information Proc. Systems , pp. 283-290
    • Dhillon, I.S.1    Sra, S.2
  • 9
    • 80055042190 scopus 로고    scopus 로고
    • Algorithms for nonnegative matrix factorization with the beta-divergence
    • abs/1010.1763
    • Févotte, C., and Idier, J. 2010. Algorithms for nonnegative matrix factorization with the beta-divergence. CoRR abs/1010.1763.
    • (2010) CoRR
    • Févotte, C.1    Idier, J.2
  • 11
    • 67349093319 scopus 로고    scopus 로고
    • Nonnegative matrix factorization based on alternating non-negativity-constrained least squares and the active set method
    • Kim, H., and Park, H. 2008. Nonnegative matrix factorization based on alternating non-negativity-constrained least squares and the active set method. SIAM Journal on Matrix Analysis and Applications 30(2):713-730.
    • (2008) SIAM Journal on Matrix Analysis and Applications , vol.30 , Issue.2 , pp. 713-730
    • Kim, H.1    Park, H.2
  • 12
    • 0033592606 scopus 로고    scopus 로고
    • Learning the parts of objects by non-negative matrix factorization
    • Lee, D. D., and Seung, H. S. 1999. Learning the parts of objects by non-negative matrix factorization. Nature 401(6755):788-791.
    • (1999) Nature , vol.401 , Issue.6755 , pp. 788-791
    • Lee, D.D.1    Seung, H.S.2
  • 14
    • 35548969471 scopus 로고    scopus 로고
    • Projected Gradient Methods for Nonnegative Matrix Factorization
    • Lin, C.-J. 2007. Projected Gradient Methods for Nonnegative Matrix Factorization. Neural Comp. 19(10):2756-2779.
    • (2007) Neural Comp. , vol.19 , Issue.10 , pp. 2756-2779
    • Lin, C.-J.1
  • 16
    • 25844488029 scopus 로고    scopus 로고
    • Document clustering using nonnegative matrix factorization
    • DOI 10.1016/j.ipm.2004.11.005, PII S0306457304001542
    • Shahnaz, F.; Berry, M.; Pauca, V.; and Plemmons, R. 2006. Document clustering using nonnegative matrix factorization. Info. Processing & Management 42(2):373-386. (Pubitemid 41394167)
    • (2006) Information Processing and Management , vol.42 , Issue.2 , pp. 373-386
    • Shahnaz, F.1    Berry, M.W.2    Pauca, V.P.3    Plemmons, R.J.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.