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Volumn 2, Issue , 2007, Pages

A method of initialization for nonnegative matrix factorization

Author keywords

Feature extraction; Matrix decomposition; Pattern classification; Pattern clustering methods; Unsupervised learning

Indexed keywords

ALGORITHMS; IMAGE ANALYSIS; MATRIX ALGEBRA; MULTIVARIANT ANALYSIS; NUMERICAL METHODS;

EID: 34547505091     PISSN: 15206149     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICASSP.2007.366291     Document Type: Conference Paper
Times cited : (15)

References (10)
  • 1
    • 0033592606 scopus 로고    scopus 로고
    • Learning the parts of objects by non-negative matrix factorization
    • D. D. Lee and H. S. Seung, "Learning the parts of objects by non-negative matrix factorization," Nature, vol. 401, pp. 788-791, 1999.
    • (1999) Nature , vol.401 , pp. 788-791
    • Lee, D.D.1    Seung, H.S.2
  • 3
    • 18444370569 scopus 로고    scopus 로고
    • Nonnegative features of spectrotemporal sounds for classfication
    • Y. -C. Cho and S. Choi, "Nonnegative features of spectrotemporal sounds for classfication," Pattern Recognition Letters, vol. 26, no. 9, pp. 1327-1336, 2005.
    • (2005) Pattern Recognition Letters , vol.26 , Issue.9 , pp. 1327-1336
    • Cho, Y.-C.1    Choi, S.2
  • 4
    • 33745711481 scopus 로고    scopus 로고
    • Monaural music source separation: Nonnegativity, sparseness, and shift-invariance
    • Charleston, South Carolina, Springer
    • M. Kim and S. Choi, "Monaural music source separation: Nonnegativity, sparseness, and shift-invariance," in Proc. lnt'l Conf. Independent Component Analysis and Blind Signal Separation, Charleston, South Carolina, 2006, pp. 617-624, Springer.
    • (2006) Proc. lnt'l Conf. Independent Component Analysis and Blind Signal Separation , pp. 617-624
    • Kim, M.1    Choi, S.2
  • 6
    • 49149085985 scopus 로고    scopus 로고
    • When does nonnegative matrix facotrization give a correct decomposition into parts?
    • MIT Press
    • D. L. Donoho and V. Stodden, "When does nonnegative matrix facotrization give a correct decomposition into parts?," in Advances in Neural Information Processing Systems. 2004, vol. 16, MIT Press.
    • (2004) Advances in Neural Information Processing Systems , vol.16
    • Donoho, D.L.1    Stodden, V.2
  • 7
    • 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, vol. 5, pp. 1457-1469, 2004.
    • (2004) Journal of Machine Learning Research , vol.5 , pp. 1457-1469
    • Hoyer, P.O.1
  • 8
    • 12344317125 scopus 로고    scopus 로고
    • Improving non-negative matrix factorizations through structured initialization
    • S. Wild, J. Curry, and A. Dougherty, "Improving non-negative matrix factorizations through structured initialization," Pattern Recognition, vol. 37, pp. 2217-2232, 2004.
    • (2004) Pattern Recognition , vol.37 , pp. 2217-2232
    • Wild, S.1    Curry, J.2    Dougherty, A.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.