메뉴 건너뛰기




Volumn , Issue , 2013, Pages 1240-1246

Exact top-k feature selection via ℓ2;0-norm constraint

Author keywords

[No Author keywords available]

Indexed keywords

AUGMENTED LAGRANGIAN METHODS; CLASSIFICATION ACCURACY; CONSTRAINED OPTIMI-ZATION PROBLEMS; EQUALITY CONSTRAINTS; FEATURE SELECTION METHODS; OBJECTIVE FUNCTIONS; REGULARIZATION PARAMETERS; SPARSITY REGULARIZATIONS;

EID: 84896061418     PISSN: 10450823     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (168)

References (26)
  • 1
    • 57749097129 scopus 로고    scopus 로고
    • A spectral regularization framework for multi-task structure learning
    • Andreas Argyriou, Charles A. Micchelli, Massimiliano Pontil, and Yiming Ying. A spectral regularization framework for multi-task structure learning. In NIPS, 2007.
    • (2007) NIPS
    • Argyriou, A.1    Micchelli, C.A.2    Pontil, M.3    Ying, Y.4
  • 2
    • 0005318783 scopus 로고
    • Constrained optimization and lagrange multiplier methods
    • Boston: Academic Press
    • D.P. Bertsekas. Constrained optimization and lagrange multiplier methods. Computer Science and Applied Mathematics, Boston: Academic Press, 1982, 1, 1982.
    • (1982) Computer Science and Applied Mathematics , vol.1 , pp. 1982
    • Bertsekas, D.P.1
  • 4
    • 84863167108 scopus 로고    scopus 로고
    • Multi-class l2, 1-norm support vector machine
    • Xiao Cai, Feiping Nie, Heng Huang, and Chris H. Q. Ding. Multi-class l2, 1-norm support vector machine. In ICDM, pages 91-100, 2011.
    • (2011) ICDM , pp. 91-100
    • Cai, X.1    Nie, F.2    Huang, H.3    Ding, C.H.Q.4
  • 5
    • 33749255817 scopus 로고    scopus 로고
    • R1-pca: Rotational invariant l1-norm principal component analysis for robust subspace factorization
    • Chris H. Q. Ding, Ding Zhou, Xiaofeng He, and Hongyuan Zha. R1-pca: rotational invariant l1-norm principal component analysis for robust subspace factorization. In ICML, pages 281-288, 2006.
    • (2006) ICML , pp. 281-288
    • Ding, C.H.Q.1    Zhou, D.2    He, X.3    Zha, H.4
  • 7
    • 0030822569 scopus 로고    scopus 로고
    • Massively parallel genomics
    • S.P. Fodor. Massively parallel genomics. Science( Washington), 277(5324):393-395, 1997.
    • (1997) Science( Washington) , vol.277 , Issue.5324 , pp. 393-395
    • Fodor, S.P.1
  • 8
    • 70349254646 scopus 로고    scopus 로고
    • Extremely fast text feature extraction for classification and indexing
    • George Forman and Evan Kirshenbaum. Extremely fast text feature extraction for classification and indexing. In CIKM, pages 1221-1230, 2008.
    • (2008) CIKM , pp. 1221-1230
    • Forman, G.1    Kirshenbaum, E.2
  • 9
    • 33745561205 scopus 로고    scopus 로고
    • An introduction to variable and feature selection
    • Isabelle Guyon and André Elisseeff. An introduction to variable and feature selection. Journal of Machine Learning Research, 3:1157-1182, 2003.
    • (2003) Journal of Machine Learning Research , vol.3 , pp. 1157-1182
    • Guyon, I.1    Elisseeff, A.2
  • 10
    • 0036161259 scopus 로고    scopus 로고
    • Gene selection for cancer classification using support vector machines
    • Isabelle Guyon, Jason Weston, Stephen Barnhill, and Vladimir Vapnik. Gene selection for cancer classification using support vector machines. Machine Learning, 46(1-3):389-422, 2002.
    • (2002) Machine Learning , vol.46 , Issue.1-3 , pp. 389-422
    • Guyon, I.1    Weston, J.2    Barnhill, S.3    Vapnik, V.4
  • 11
    • 0000364411 scopus 로고
    • Selection of variables in discriminant analysis by F-statistic and error rate
    • JDF Habbema and J. Hermans. Selection of variables in discriminant analysis by F-statistic and error rate. Technometrics, 19(4):487-493, 1977.
    • (1977) Technometrics , vol.19 , Issue.4 , pp. 487-493
    • Habbema, J.1    Hermans, J.2
  • 12
    • 4043059226 scopus 로고    scopus 로고
    • Feature selection for machine learning: Comparing a correlation-based filter approach to the wrapper
    • Mark A. Hall and Lloyd A. Smith. Feature selection for machine learning: Comparing a correlation-based filter approach to the wrapper. In FLAIRS Conference, pages 235-239, 1999.
    • (1999) FLAIRS Conference , pp. 235-239
    • Hall, M.A.1    Smith, L.A.2
  • 13
    • 85146422424 scopus 로고
    • A practical approach to feature selection
    • Kenji Kira and Larry A. Rendell. A practical approach to feature selection. In ML, pages 249-256, 1992.
    • (1992) ML , pp. 249-256
    • Kira, K.1    Rendell, L.A.2
  • 14
    • 0031381525 scopus 로고    scopus 로고
    • Wrappers for feature subset selection
    • Ron Kohavi and George H. John. Wrappers for feature subset selection. Artif. Intell., 97(1-2):273-324, 1997.
    • (1997) Artif. Intell , vol.97 , Issue.1-2 , pp. 273-324
    • Kohavi, R.1    John, G.H.2
  • 15
    • 79951737392 scopus 로고    scopus 로고
    • Towards structural sparsity: An explicit l2/l0 approach
    • Dijun Luo, Chris H. Q. Ding, and Heng Huang. Towards structural sparsity: An explicit l2/l0 approach. In ICDM, pages 344-353, 2010.
    • (2010) ICDM , pp. 344-353
    • Luo, D.1    Ding, C.H.Q.2    Huang, H.3
  • 16
    • 78649867587 scopus 로고    scopus 로고
    • L0-norm-based sparse representation through alternate projections
    • Luis Mancera and Javier Portilla. L0-norm-based sparse representation through alternate projections. In ICIP, pages 2089-2092, 2006.
    • (2006) ICIP , pp. 2089-2092
    • Mancera, L.1    Portilla, J.2
  • 17
    • 85135939782 scopus 로고    scopus 로고
    • Efficient and robust feature selection via joint ;2, 1-norms minimization
    • Feiping Nie, Heng Huang, Xiao Cai, and Chris H. Q. Ding. Efficient and robust feature selection via joint ;2, 1-norms minimization. In NIPS, pages 1813-1821, 2010.
    • (2010) NIPS , pp. 1813-1821
    • Nie, F.1    Huang, H.2    Cai, X.3    Ding, C.H.Q.4
  • 19
    • 77953322499 scopus 로고    scopus 로고
    • Joint covariate selection and joint subspace selection for multiple classification problems
    • Guillaume Obozinski, Ben Taskar, and Michael I. Jordan. Joint covariate selection and joint subspace selection for multiple classification problems. Statistics and Computing, 20(2):231-252, 2010.
    • (2010) Statistics and Computing , vol.20 , Issue.2 , pp. 231-252
    • Obozinski, G.1    Taskar, B.2    Jordan, M.I.3
  • 20
    • 24344458137 scopus 로고    scopus 로고
    • Feature selection based on mutual information: Criteria of max-dependency, max-relevance, and min-redundancy
    • Hanchuan Peng, Fuhui Long, and Chris H. Q. Ding. Feature selection based on mutual information: Criteria of max-dependency, max-relevance, and min-redundancy. IEEE Trans. Pattern Anal. Mach. Intell., 27(8):1226-1238, 2005.
    • (2005) IEEE Trans. Pattern Anal. Mach. Intell , vol.27 , Issue.8 , pp. 1226-1238
    • Peng, H.1    Long, F.2    Ding, C.H.Q.3
  • 21
    • 0002380692 scopus 로고
    • A method for nonlinear constraints in minimization problems
    • R. Fletcher, editor, Academic Press, London and New York
    • M. J. D. Powell. A method for nonlinear constraints in minimization problems. In R. Fletcher, editor, Optimization. Academic Press, London and New York, 1969.
    • (1969) Optimization
    • Powell, M.J.D.1
  • 22
    • 3943113604 scopus 로고    scopus 로고
    • Theoretical comparison between the gini index and information gain criteria
    • Laura Elena Raileanu and Kilian Stoffel. Theoretical comparison between the gini index and information gain criteria. Ann. Math. Artif. Intell., 41(1):77-93, 2004.
    • (2004) Ann. Math. Artif. Intell , vol.41 , Issue.1 , pp. 77-93
    • Elena Raileanu, L.1    Stoffel, K.2
  • 23
    • 35748932917 scopus 로고    scopus 로고
    • A review of feature selection techniques in bioinformatics
    • Yvan Saeys, Iñaki Inza, and Pedro Larrañaga. A review of feature selection techniques in bioinformatics. Bioinformatics, 23(19):2507-2517, 2007.
    • (2007) Bioinformatics , vol.23 , Issue.19 , pp. 2507-2517
    • Saeys, Y.1    Inza, I.2    Larrañaga, P.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.