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Volumn , Issue , 2004, Pages 241-248

The Bayesian backfitting relevance vector machine

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMPUTATIONAL METHODS; LEAST SQUARES APPROXIMATIONS; PROBABILITY; REGRESSION ANALYSIS; STATISTICAL METHODS; VECTORS;

EID: 14344261138     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (19)

References (18)
  • 3
    • 4544371135 scopus 로고    scopus 로고
    • Dimensionality reduction for supervised learning using re producing kernel Hubert spaces
    • Fukumizu, K., Bach, F. R., & Jordan, M. I. (2004). Dimensionality reduction for supervised learning using re producing kernel Hubert spaces. Journal of Machine Learning Research, 5, 73-99.
    • (2004) Journal of Machine Learning Research , vol.5 , pp. 73-99
    • Fukumizu, K.1    Bach, F.R.2    Jordan, M.I.3
  • 4
    • 84898934543 scopus 로고    scopus 로고
    • Variational inference for Bayesian mixtures of factor analysers
    • Cambridge, MA: MIT Press
    • Ghahramani, Z., & Beal, M. J. (2000). Variational inference for Bayesian mixtures of factor analysers. Advances in Neural Information Processing Systems 12 (pp. 509-514). Cambridge, MA: MIT Press.
    • (2000) Advances in Neural Information Processing Systems , vol.12 , pp. 509-514
    • Ghahramani, Z.1    Beal, M.J.2
  • 5
    • 0003598526 scopus 로고
    • No. 43 in Monographs on Statistics and Applied Probability. Chapman & Hall
    • Hastie, T. J., & Tibshirani, R. J. (1990). Generalized additive models. No. 43 in Monographs on Statistics and Applied Probability. Chapman & Hall.
    • (1990) Generalized Additive Models
    • Hastie, T.J.1    Tibshirani, R.J.2
  • 6
    • 0042685161 scopus 로고    scopus 로고
    • Bayesian parameter estimation via variational methods
    • Jaakkola, T. S., &: Jordan, M. I. (2000). Bayesian parameter estimation via variational methods. Statistics and Computing, 10, 25-37.
    • (2000) Statistics and Computing , vol.10 , pp. 25-37
    • Jaakkola, T.S.1    Jordan, M.I.2
  • 8
    • 0000597408 scopus 로고    scopus 로고
    • Comparison of approximate methods for handling hyperparameters
    • MacKay, D. J. C. (1999). Comparison of approximate methods for handling hyperparameters. Neural Computation, 11, 1035-1068.
    • (1999) Neural Computation , vol.11 , pp. 1035-1068
    • MacKay, D.J.C.1
  • 9
    • 0000957593 scopus 로고
    • Principal component regression in exploratory statistical research
    • Massey, W. F. (1965). Principal component regression in exploratory statistical research. Journal of the American Statistical Association, 60, 234-246.
    • (1965) Journal of the American Statistical Association , vol.60 , pp. 234-246
    • Massey, W.F.1
  • 10
    • 0003611509 scopus 로고
    • Doctoral dissertation, Dept. of Computer Science, University of Toronto
    • Neal, R. M. (1994). Bayesian learning for neural networks. Doctoral dissertation, Dept. of Computer Science, University of Toronto.
    • (1994) Bayesian Learning for Neural Networks
    • Neal, R.M.1
  • 13
    • 0001224048 scopus 로고    scopus 로고
    • Sparse Bayesian learning and the relevance vector machine
    • Tipping, M. E. (2001). Sparse Bayesian learning and the relevance vector machine. Journal of Machine Learning Research, 1, 211-244.
    • (2001) Journal of Machine Learning Research , vol.1 , pp. 211-244
    • Tipping, M.E.1
  • 18
    • 0002692783 scopus 로고
    • Soft modeling by latent variables: The nonlinear iterative partial least squares approach
    • J. Gani (Ed.). London: Academic Press
    • Wold, H. (1975). Soft modeling by latent variables: The nonlinear iterative partial least squares approach. In J. Gani (Ed.), Perspectives in probability and statistics, papers in honour of M. S. Bartlett, 520-540. London: Academic Press.
    • (1975) Perspectives in Probability and Statistics, Papers in Honour of M. S. Bartlett , pp. 520-540
    • Wold, H.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.