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Volumn 2015-January, Issue , 2015, Pages 3576-3582

Scalable Gaussian process regression using deep neural networks

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; GAUSSIAN NOISE (ELECTRONIC); MAPPING; REGRESSION ANALYSIS;

EID: 84949813690     PISSN: 10450823     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (72)

References (26)
  • 6
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    • Reducing the dimensionality of data with neural networks
    • July
    • G E Hinton and R R Salakhutdinov. Reducing the dimensionality of data with neural networks. Science, 313(5786):504-507, July 2006.
    • (2006) Science , vol.313 , Issue.5786 , pp. 504-507
    • Hinton, G.E.1    Salakhutdinov, R.R.2
  • 7
    • 33745805403 scopus 로고    scopus 로고
    • A fast learning algorithm for deep belief nets
    • G. E. Hinton, S. Osindero, and Y. W. Teh. A fast learning algorithm for deep belief nets. Neural Computation, 18:1527-1554, 2006.
    • (2006) Neural Computation , vol.18 , pp. 1527-1554
    • Hinton, G.E.1    Osindero, S.2    Teh, Y.W.3
  • 9
    • 85156260506 scopus 로고    scopus 로고
    • Fast sparse Gaussian process methods: The informative vector machine
    • Suzanna Becker, Sebastian Thrun, and Klaus Obermayer, editors
    • Neil D. Lawrence, Matthias Seeger, and Ralf Herbrich. Fast sparse Gaussian process methods: the informative vector machine. In Suzanna Becker, Sebastian Thrun, and Klaus Obermayer, editors, Advances in Neural Information Processing Systems (NIPS), pages 609-616, 2002.
    • (2002) Advances in Neural Information Processing Systems (NIPS) , pp. 609-616
    • Lawrence, N.D.1    Seeger, M.2    Herbrich, R.3
  • 12
    • 85048514667 scopus 로고    scopus 로고
    • The generalized FITC approximation
    • John C. Platt, Daphne Koller, Yoram Singer, and Sam T. Roweis, editors
    • Andrew Naish-Guzman and Sean B. Holden. The generalized FITC approximation. In John C. Platt, Daphne Koller, Yoram Singer, and Sam T. Roweis, editors, Advances in Neural Information Processing Systems (NIPS), 2007.
    • (2007) Advances in Neural Information Processing Systems (NIPS)
    • Naish-Guzman, A.1    Holden, S.B.2
  • 14
    • 56349122110 scopus 로고    scopus 로고
    • Approximations for binary Gaussian process classification
    • October
    • Hannes Nickisch and Carl Edward Rasmussen. Approximations for binary Gaussian process classification. Journal of Machine Learning Research (JMLR), 9:2035-2078, October 2008.
    • (2008) Journal of Machine Learning Research (JMLR) , vol.9 , pp. 2035-2078
    • Nickisch, H.1    Rasmussen, C.E.2
  • 17
    • 84937442245 scopus 로고    scopus 로고
    • Using deep belief nets to learn covariance kernels for Gaussian processes
    • John C. Platt, Daphne Koller, Yoram Singer, and Sam T. Roweis, editors
    • Ruslan Salakhutdinov and Geoffrey E. Hinton. Using deep belief nets to learn covariance kernels for Gaussian processes. In John C. Platt, Daphne Koller, Yoram Singer, and Sam T. Roweis, editors, Advances in Neural Information Processing Systems (NIPS), 2007.
    • (2007) Advances in Neural Information Processing Systems (NIPS)
    • Salakhutdinov, R.1    Hinton, G.E.2
  • 19
    • 12444291490 scopus 로고    scopus 로고
    • Gaussian processes for machine learning
    • Matthias Seeger. Gaussian processes for machine learning. International Journal of Neural Systems., 14(2):69-106, 2004.
    • (2004) International Journal of Neural Systems , vol.14 , Issue.2 , pp. 69-106
    • Seeger, M.1
  • 20
    • 0003275056 scopus 로고    scopus 로고
    • Sparse greedy Gaussian process regression
    • Todd K. Leen, Thomas G. Dietterich, and Volker Tresp, editors
    • Alex J. Smola and Peter L. Bartlett. Sparse greedy Gaussian process regression. In Todd K. Leen, Thomas G. Dietterich, and Volker Tresp, editors, Advances in Neural Information Processing Systems (NIPS), pages 619-625, 2000.
    • (2000) Advances in Neural Information Processing Systems (NIPS) , pp. 619-625
    • Smola, A.J.1    Bartlett, P.L.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.