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Volumn , Issue , 2013, Pages

A comparative framework for Preconditioned Lasso algorithms

Author keywords

[No Author keywords available]

Indexed keywords

MULTIVARIANT ANALYSIS;

EID: 84898935613     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (15)

References (15)
  • 1
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    • Stable recovery of sparse overcomplete representations in the presence of noise
    • D.L. Donoho, M. Elad, and V.N. Temlyakov. Stable recovery of sparse overcomplete representations in the presence of noise. Information Theory, IEEE Transactions on, 52(1):6-18, 2006.
    • (2006) Information Theory. IEEE Transactions on , vol.52 , Issue.1 , pp. 6-18
    • Donoho, D.L.1    Elad, M.2    Temlyakov, V.N.3
  • 2
    • 1542784498 scopus 로고    scopus 로고
    • Variable selection via nonconcave penalized likelihood and its oracle properties
    • J. Fan and R. Li. Variable selection via nonconcave penalized likelihood and its oracle properties. Journal of the American Statistical Association, 96:1348-1360, 2001.
    • (2001) Journal of the American Statistical Association , vol.96 , pp. 1348-1360
    • Fan, J.1    Li, R.2
  • 3
    • 26844461512 scopus 로고    scopus 로고
    • Recovery of exact sparse representations in the presence of bounded noise
    • J.J. Fuchs. Recovery of exact sparse representations in the presence of bounded noise. Information Theory, IEEE Transactions on, 51(10):3601-3608, 2005.
    • (2005) Information Theory IEEE Transactions on , vol.51 , Issue.10 , pp. 3601-3608
    • Fuchs, J.J.1
  • 5
    • 79953195127 scopus 로고    scopus 로고
    • Variable selection through Correlation Sifting
    • V. Bafna and S.C. Sahinalp, editors, volume 6577 of Lecture Notes in Computer Science, Springer
    • J.C. Huang and N. Jojic. Variable selection through Correlation Sifting. In V. Bafna and S.C. Sahinalp, editors, RECOMB, volume 6577 of Lecture Notes in Computer Science, pages 106-123. Springer, 2011.
    • (2011) RECOMB , pp. 106-123
    • Huang, J.C.1    Jojic, N.2
  • 7
    • 33745181295 scopus 로고    scopus 로고
    • Lasso with relaxation
    • Eidgenössische Technische Hochschule, Zürich
    • N. Meinshausen. Lasso with relaxation. Technical Report 129, Eidgenössische Technische Hochschule, Zürich, 2005.
    • (2005) Technical Report 129
    • Meinshausen, N.1
  • 8
    • 33747163541 scopus 로고    scopus 로고
    • High-dimensional graphs and variable selection with the Lasso
    • N. Meinshausen and P. Bühlmann. High-dimensional graphs and variable selection with the Lasso. Annals of Statistics, 34(3):1436-1462, 2006.
    • (2006) Annals of Statistics , vol.34 , Issue.3 , pp. 1436-1462
    • Meinshausen, N.1    Bühlmann, P.2
  • 9
    • 51049112528 scopus 로고    scopus 로고
    • "Preconditioning" for feature selection and regression in high-dimensional problems
    • D. Paul, E. Bair, T. Hastie, and R. Tibshirani. " Preconditioning" for feature selection and regression in high-dimensional problems. Annals of Statistics, 36(4):1595-1618, 2008.
    • (2008) Annals of Statistics , vol.36 , Issue.4 , pp. 1595-1618
    • Paul, D.1    Bair, E.2    Hastie, T.3    Tibshirani, R.4
  • 12
    • 65749083666 scopus 로고    scopus 로고
    • Sharp thresholds for high-dimensional and noisy sparsity recovery using ℓ1-constrained quadratic programming (Lasso)
    • M.J. Wainwright. Sharp thresholds for high-dimensional and noisy sparsity recovery using ℓ1-constrained quadratic programming (Lasso). IEEE Transactions on Information Theory, 55(5):2183-2202, 2009.
    • (2009) IEEE Transactions on Information Theory , vol.55 , Issue.5 , pp. 2183-2202
    • Wainwright, M.J.1
  • 13


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.