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Volumn , Issue , 2011, Pages 545-552

Linear regression under fixed-rank constraints: A Riemannian approach

Author keywords

[No Author keywords available]

Indexed keywords

HIGH-DIMENSIONAL PROBLEMS; LINE SEARCH ALGORITHM; LINEAR REGRESSION MODELS; LOCAL CONVERGENCE; MATRIX; NUMERICAL EXPERIMENTS; RIEMANNIAN MANIFOLD;

EID: 80053443288     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (65)

References (21)
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    • Abernethy, J.1    Bach, F.2    Evgeniou, T.3    Vert, J.-P.4
  • 4
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    • Consistency of trace norm minimization
    • Bach, F. Consistency of trace norm minimization. Journal of Machine Learning Research, 9(Jun):1019-1048, 2008.
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    • Bach, F.1
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    • 69849094133 scopus 로고    scopus 로고
    • Supervised prediction of drug-target interactions using bipartite local models
    • Bleakley, K. and Yamanishi, Y. Supervised prediction of drug-target interactions using bipartite local models. Bioinformatics, 25(18):2397-2403, 2009.
    • (2009) Bioinformatics , vol.25 , Issue.18 , pp. 2397-2403
    • Bleakley, K.1    Yamanishi, Y.2
  • 8
    • 77951291046 scopus 로고    scopus 로고
    • A singular value thresholding algorithm for matrix completion
    • Cai, J.-F., Candes, E. J., and Shen, Z. A singular value thresholding algorithm for matrix completion. SIAM Journal on Optimization, 20(4):1956-1982, 2008.
    • (2008) SIAM Journal on Optimization , vol.20 , Issue.4 , pp. 1956-1982
    • Cai, J.-F.1    Candes, E.J.2    Shen, Z.3
  • 9
    • 84966217951 scopus 로고
    • Reorthogonalization and stable algorithms for updating the Gram-Schmidt QR factorization
    • Daniel, J., Gragg, W.B., Kaufman, L., and Stewart, G. W. Reorthogonalization and stable algorithms for updating the Gram-Schmidt QR factorization. Math. Comp., 30:772-795, 1976.
    • (1976) Math. Comp. , vol.30 , pp. 772-795
    • Daniel, J.1    Gragg, W.B.2    Kaufman, L.3    Stewart, G.W.4
  • 15
    • 77955747588 scopus 로고    scopus 로고
    • Admira: Atomic decomposition for minimum rank approximation
    • Lee, K. and Bresler, Y. Admira: Atomic decomposition for minimum rank approximation. IEEE Trans. on Information Theory, 56(9):4402-4416, 2010.
    • (2010) IEEE Trans. on Information Theory , vol.56 , Issue.9 , pp. 4402-4416
    • Lee, K.1    Bresler, Y.2
  • 16
    • 79952746338 scopus 로고    scopus 로고
    • Regression on fixed-rank positive semidefinite matrices: A Riemannian approach
    • Meyer, G., Bonnabel, S., and Sepulchre, R. Regression on fixed-rank positive semidefinite matrices: a Riemannian approach. Journal of Machine Learning Research, 12(Feb):593-625, 2011.
    • (2011) Journal of Machine Learning Research , vol.12 , Issue.FEB , pp. 593-625
    • Meyer, G.1    Bonnabel, S.2    Sepulchre, R.3
  • 18
    • 78549288866 scopus 로고    scopus 로고
    • Guaranteed minimum-rank solutions of linear matrix equations via nuclear norm minimization
    • August
    • Recht, B., Fazel, M., and Parrilo, P. A. Guaranteed minimum-rank solutions of linear matrix equations via nuclear norm minimization. SIAM Review, 53(3):471-501, August 2010.
    • (2010) SIAM Review , vol.53 , Issue.3 , pp. 471-501
    • Recht, B.1    Fazel, M.2    Parrilo, P.A.3
  • 21
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    • Grassmann algorithms for low rank approximation of matrices with missing values
    • Simonsson, L. and Eldén, L. Grassmann algorithms for low rank approximation of matrices with missing values. BIT Numerical Math., 50(1):173-191, 2010.
    • (2010) BIT Numerical Math. , vol.50 , Issue.1 , pp. 173-191
    • Simonsson, L.1    Eldén, L.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.