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Volumn , Issue , 2009, Pages 1141-1149

Nonparametric greedy algorithms for the sparse learning problem

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; LEARNING ALGORITHMS;

EID: 84863337862     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (10)

References (23)
  • 1
    • 46249088758 scopus 로고    scopus 로고
    • Consistency of the group lasso and multiple kernel learning
    • Francis Bach. Consistency of the group lasso and multiple kernel learning. Journal of Machine Learning Research, 8:1179-1225, 2008.
    • (2008) Journal of Machine Learning Research , vol.8 , pp. 1179-1225
    • Bach, F.1
  • 2
    • 84858766876 scopus 로고    scopus 로고
    • Exploring large feature spaces with hierarchical multiple kernel learning
    • MIT Press
    • Francis Bach. Exploring large feature spaces with hierarchical multiple kernel learning. In Advances in Neural Information Processing Systems 21. MIT Press, 2008.
    • (2008) Advances in Neural Information Processing Systems , vol.21
    • Bach, F.1
  • 6
    • 34548275795 scopus 로고    scopus 로고
    • The dantzig selector: Statistical estimation when p is much larger than n
    • Emmanuel Candes and Terence Tao. The dantzig selector: statistical estimation when p is much larger than n. The Annals of Statistics, 35:2313-2351, 2007.
    • (2007) The Annals of Statistics , vol.35 , pp. 2313-2351
    • Candes, E.1    Tao, T.2
  • 9
    • 0002432565 scopus 로고
    • Multivariate adaptive regression splines
    • Jerome H. Friedman. Multivariate adaptive regression splines. The Annals of Statistics, 19:1-67, 1991.
    • (1991) The Annals of Statistics , vol.19 , pp. 1-67
    • Friedman, J.H.1
  • 11
    • 50649123582 scopus 로고    scopus 로고
    • Rodeo: Sparse, greedy nonparametric regression
    • John Lafferty and Larry Wasserman. Rodeo: Sparse, greedy nonparametric regression. The Annals of Statistics, 36(1):28-63, 2008.
    • (2008) The Annals of Statistics , vol.36 , Issue.1 , pp. 28-63
    • Lafferty, J.1    Wasserman, L.2
  • 12
    • 33847350805 scopus 로고    scopus 로고
    • Component selection and smoothing in multivariate nonpara-metric regression
    • Yi Lin and Hao Helen Zhang. Component selection and smoothing in multivariate nonpara-metric regression. The Annals of Statistics., 34(5):2272-2297, 2006.
    • (2006) The Annals of Statistics , vol.34 , Issue.5 , pp. 2272-2297
    • Lin, Y.1    Zhang, H.H.2
  • 18
    • 0000997747 scopus 로고
    • Spline smoothing: The equivalent variable kernel method
    • B. W. Silverman. Spline smoothing: The equivalent variable kernel method. The Annals of Statistics, 12:898-916, 1984.
    • (1984) The Annals of Statistics , vol.12 , pp. 898-916
    • Silverman, B.W.1
  • 20
    • 5444237123 scopus 로고    scopus 로고
    • Greed is good: Algorithmic results for sparse approximation
    • October
    • Joel A. Tropp. Greed is good: Algorithmic results for sparse approximation. IEEE Trans. Inform. Theory, 50(10):2231-2241, October 2004.
    • (2004) IEEE Trans. Inform. Theory , vol.50 , Issue.10 , pp. 2231-2241
    • Tropp, J.A.1
  • 22
    • 85162012518 scopus 로고    scopus 로고
    • Adaptive forward-backward greedy algorithm for learning sparse representations
    • Tong Zhang. Adaptive forward-backward greedy algorithm for learning sparse representations. Technical report, Rutgers University, 2008.
    • (2008) Technical Report, Rutgers University
    • Tong, Z.1
  • 23
    • 64149088421 scopus 로고    scopus 로고
    • On the consistency of feature selection usinggreedy least squares regression
    • Tong Zhang. On the consistency of feature selection usinggreedy least squares regression. Journal of Machine Learning Research, 10:555-568, 2009.
    • (2009) Journal of Machine Learning Research , vol.10 , pp. 555-568
    • Tong, Z.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.