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Volumn 171, Issue 2, 2005, Pages 1264-1281

Exploiting Hessian matrix and trust-region algorithm in hyperparameters estimation of Gaussian process

Author keywords

Conjugate gradient; Gaussian process; Hessian matrix; Log likelihood maximization; Trust region

Indexed keywords

ALGORITHMS; MATHEMATICAL MODELS; OPTIMIZATION; PARAMETER ESTIMATION; REGRESSION ANALYSIS;

EID: 31144441548     PISSN: 00963003     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.amc.2005.01.113     Document Type: Article
Times cited : (44)

References (28)
  • 1
    • 0024880831 scopus 로고
    • Multilayer feedforward networks are universal approximators
    • K. Hornik, M. Stinchcombe, and H. White Multilayer feedforward networks are universal approximators Neural Networks 2 1989 259 366
    • (1989) Neural Networks , vol.2 , pp. 259-366
    • Hornik, K.1    Stinchcombe, M.2    White, H.3
  • 2
    • 0001160588 scopus 로고
    • What size net gives valid generalization?
    • E.B. Baum, and D. Haussler What size net gives valid generalization? Neural Computation 6 1989 151 160
    • (1989) Neural Computation , vol.6 , pp. 151-160
    • Baum, E.B.1    Haussler, D.2
  • 3
    • 0003301456 scopus 로고    scopus 로고
    • Bayesian learning for neural networks
    • Springer New York
    • R.M. Neal Bayesian learning for neural networks Lecture notes in statistics 118 1996 Springer New York
    • (1996) Lecture Notes in Statistics , vol.118
    • Neal, R.M.1
  • 12
    • 84949108850 scopus 로고    scopus 로고
    • Direct identification of nonlinear structure using Gaussian process prior models
    • Cambridge
    • W.E. Leithead, E. Solak, D.J. Leith, Direct identification of nonlinear structure using Gaussian process prior models, in: European Control Conference, Cambridge, 2003.
    • (2003) European Control Conference
    • Leithead, W.E.1    Solak, E.2    Leith, D.J.3
  • 14
    • 0001196683 scopus 로고
    • Maximum likelihood estimation for models of residual covariance in spatial regression
    • K.V. Mardia, and R.J. Marshall Maximum likelihood estimation for models of residual covariance in spatial regression Biometrika 71 1984 135 146
    • (1984) Biometrika , vol.71 , pp. 135-146
    • Mardia, K.V.1    Marshall, R.J.2
  • 17
    • 84972047841 scopus 로고
    • Theory of algorithms for unconstrained optimization
    • J. Nocedal Theory of algorithms for unconstrained optimization Acta Numerica 1992 199 242
    • (1992) Acta Numerica , pp. 199-242
    • Nocedal, J.1
  • 18
    • 0027205884 scopus 로고
    • A scaled conjugate gradient algorithm for fast supervised learning
    • M.F. Moller A scaled conjugate gradient algorithm for fast supervised learning Neural Networks 6 1993 525 533
    • (1993) Neural Networks , vol.6 , pp. 525-533
    • Moller, M.F.1
  • 21
    • 0034757837 scopus 로고    scopus 로고
    • A fast Newton method for entropy maximization in statistical phase estimation
    • Z. Wu, G.N. Phillips Jr., R. Tapia, and Y. Zhang A fast Newton method for entropy maximization in statistical phase estimation Acta Crystallographica A 57 2001 681 685
    • (2001) Acta Crystallographica A , vol.57 , pp. 681-685
    • Wu, Z.1    Phillips Jr., G.N.2    Tapia, R.3    Zhang, Y.4
  • 25
    • 0000305846 scopus 로고
    • The conjugate gradient method and trust regions in large scale optimization
    • T. Steihaug The conjugate gradient method and trust regions in large scale optimization SIAM Journal on Numerical Analysis 20 1983 626 637
    • (1983) SIAM Journal on Numerical Analysis , vol.20 , pp. 626-637
    • Steihaug, T.1
  • 26
    • 34250095268 scopus 로고
    • Approximate solution of the trust region problem by minimization over two-dimensional subspaces
    • R.H. Byrd, R.B. Schnabel, and G.A. Shultz Approximate solution of the trust region problem by minimization over two-dimensional subspaces Mathematical Programming 40 1988 247 263
    • (1988) Mathematical Programming , vol.40 , pp. 247-263
    • Byrd, R.H.1    Schnabel, R.B.2    Shultz, G.A.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.