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Volumn , Issue , 2010, Pages

CUR from a sparse optimization viewpoint

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE;

EID: 85162015690     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (44)

References (21)
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    • A direct formulation for sparse PCA using semidefinite programming
    • A. d'Aspremont, L. El Ghaoui, M. I. Jordan, and G. R. G. Lanckriet. A direct formulation for sparse PCA using semidefinite programming. SIAM Review, 49(3):434-448, 2007.
    • (2007) SIAM Review , vol.49 , Issue.3 , pp. 434-448
    • D'aspremont, A.1    El Ghaoui, L.2    Jordan, M.I.3    Lanckriet, G.R.G.4
  • 3
    • 33751097630 scopus 로고    scopus 로고
    • Fast Monte Carlo algorithms for matrices III: Computing a compressed approximate matrix decomposition
    • P. Drineas, R. Kannan, and M.W. Mahoney. Fast Monte Carlo algorithms for matrices III: Computing a compressed approximate matrix decomposition. SIAM Journal on Computing, 36:184-206, 2006.
    • (2006) SIAM Journal on Computing , vol.36 , pp. 184-206
    • Drineas, P.1    Kannan, R.2    Mahoney, M.W.3
  • 5
    • 0037790752 scopus 로고    scopus 로고
    • The maximum-volume concept in approximation by low-rank matrices
    • S.A. Goreinov and E.E. Tyrtyshnikov. The maximum-volume concept in approximation by low-rank matrices. Contemporary Mathematics, 280:47-51, 2001.
    • (2001) Contemporary Mathematics , vol.280 , pp. 47-51
    • Goreinov, S.A.1    Tyrtyshnikov, E.E.2
  • 8
    • 84948783167 scopus 로고
    • The hat matrix in regression and ANOVA
    • D.C. Hoaglin and R.E. Welsch. The hat matrix in regression and ANOVA. The American Statistician, 32(1):17-22, 1978.
    • (1978) The American Statistician , vol.32 , Issue.1 , pp. 17-22
    • Hoaglin, D.C.1    Welsch, R.E.2
  • 12
    • 58849086813 scopus 로고    scopus 로고
    • CUR matrix decompositions for improved data analysis
    • M.W. Mahoney and P. Drineas. CUR matrix decompositions for improved data analysis. Proc. Natl. Acad. Sci. USA, 106:697-702, 2009.
    • (2009) Proc. Natl. Acad. Sci. USA , vol.106 , pp. 697-702
    • Mahoney, M.W.1    Drineas, P.2
  • 19
    • 70149096300 scopus 로고    scopus 로고
    • A penalized matrix decomposition, with applications to sparse principal components and canonical correlation analysis
    • D. M. Witten, R. Tibshirani, and T. Hastie. A penalized matrix decomposition, with applications to sparse principal components and canonical correlation analysis. Biostatistics, 10(3):515-534, 2009.
    • (2009) Biostatistics , vol.10 , Issue.3 , pp. 515-534
    • Witten, D.M.1    Tibshirani, R.2    Hastie, T.3
  • 20
    • 33645035051 scopus 로고    scopus 로고
    • Model selection and estimation in regression with grouped variables
    • M. Yuan and Y. Lin. Model selection and estimation in regression with grouped variables. Journal of the Royal Statistical Society: Series B, 68(1):49-67, 2006.
    • (2006) Journal of the Royal Statistical Society: Series B , vol.68 , Issue.1 , pp. 49-67
    • Yuan, M.1    Lin, Y.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.