메뉴 건너뛰기




Volumn 72, Issue 13-15, 2009, Pages 2824-2832

Finding optimal model parameters by deterministic and annealed focused grid search

Author keywords

Annealing; CMA ES; Evolutive algorithms; Grid search; Optimal parameters

Indexed keywords

ANNEALING; COVARIANCE MATRIX; EVOLUTIONARY ALGORITHMS; PARAMETER ESTIMATION;

EID: 77955516396     PISSN: 09252312     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neucom.2008.09.024     Document Type: Article
Times cited : (41)

References (22)
  • 4
    • 0036738840 scopus 로고    scopus 로고
    • Efficient tuning of SVM hyperparameters using radius/margin bound and iterative algorithms
    • S.S. Keerthi, Efficient tuning of SVM hyperparameters using radius/margin bound and iterative algorithms, IEEE Transactions on Neural Networks 13 (5) (2002)1225-1229.
    • (2002) IEEE Transactions on Neural Networks , vol.13 , Issue.5 , pp. 1225-1229
    • Keerthi, S.S.1
  • 7
    • 20344404925 scopus 로고    scopus 로고
    • Parameter selection for support vector machines
    • HP Laboratories, Israel
    • C. Staelin, Parameter selection for support vector machines, Technical Report HPL-2002-354, HP Laboratories, Israel, 2000.
    • (2000) Technical Report HPL-2002-354
    • Staelin, C.1
  • 8
    • 6344287812 scopus 로고    scopus 로고
    • A review of genetic algorithms applied to training radial basis function networks
    • C. Harpham, C.W. Dawson, M.R. Brown, A review of genetic algorithms applied to training radial basis function networks, Neural Computing & Applications 13 (3) (2004) 193-201.
    • (2004) Neural Computing & Applications , vol.13 , Issue.3 , pp. 193-201
    • Harpham, C.1    Dawson, C.W.2    Brown, M.R.3
  • 9
    • 0028564555 scopus 로고
    • Using genetic algorithms to estimate the optimum width parameter in radial basis function networks
    • Baltimore, MD, June
    • L.E. Kuo, S.S. Melsheimer, Using genetic algorithms to estimate the optimum width parameter in radial basis function networks, in: Proceedings of the American Control Conference, Baltimore, MD, June 1994.
    • (1994) Proceedings of the American Control Conference
    • Kuo, L.E.1    Melsheimer, S.S.2
  • 10
    • 29144521785 scopus 로고    scopus 로고
    • The genetic kernel support vector machine: Description and evaluation
    • T. Howley, M.G. Madden, The genetic kernel support vector machine: description and evaluation, Artificial Intelligence Review 24 (3-4) (2005) 379-395.
    • (2005) Artificial Intelligence Review , vol.24 , Issue.3-4 , pp. 379-395
    • Howley, T.1    Madden, M.G.2
  • 12
    • 0035377566 scopus 로고    scopus 로고
    • Completely derandomized self-adaptation in evolution strategies
    • N. Hansen, A. Ostermeier, Completely derandomized self-adaptation in evolution strategies, Evolutionary Computation 9 (2) (2001) 159-195.
    • (2001) Evolutionary Computation , vol.9 , Issue.2 , pp. 159-195
    • Hansen, N.1    Ostermeier, A.2
  • 15
    • 15844394276 scopus 로고    scopus 로고
    • Evolutionary tuning of multiple SVM parameters
    • F. Friedrichs, C. Igel, Evolutionary tuning of multiple SVM parameters, Neurocomputing 64 (2005) 107-117.
    • (2005) Neurocomputing , vol.64 , pp. 107-117
    • Friedrichs, F.1    Igel, C.2
  • 17
    • 67649664260 scopus 로고    scopus 로고
    • Uniform experimental designs and their applications in industry
    • K.T. Fang, D.K.J. Lin, Uniform experimental designs and their applications in industry, Handbook of Statistics 22 (2003) 131-170.
    • (2003) Handbook of Statistics , vol.22 , pp. 131-170
    • Fang, K.T.1    Lin, D.K.J.2
  • 18
    • 75349093015 scopus 로고    scopus 로고
    • The Uniform Design Association of China
    • The Uniform Design Association of China, Uniform design tables 〈http://www.math.hkbu.edu.hk/UniformDesign/〉.
    • Uniform design tables


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.