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Volumn , Issue , 2008, Pages

The generalized FITC approximation

Author keywords

[No Author keywords available]

Indexed keywords

BENCHMARK PROBLEMS; BINARY CLASSIFICATION PROBLEMS; COVARIANCE STRUCTURES; GAUSSIAN PROCESS MODELS; GAUSSIAN PROCESS PRIORS; GENERALISATION; INFORMATIVE VECTOR MACHINES; SPARSE METHODS; STABLE ALGORITHMS; TRAINING COMPLEXITY;

EID: 85162029278     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (71)

References (17)
  • 3
    • 0034320350 scopus 로고    scopus 로고
    • Gaussian processes for classification: Mean field methods
    • Manfred Opper and Ole Winther. Gaussian processes for classification: mean field methods. Neural Computation, 12(11):2655-2684, 2000.
    • (2000) Neural Computation , vol.12 , Issue.11 , pp. 2655-2684
    • Opper, M.1    Winther, O.2
  • 4
    • 0034320395 scopus 로고    scopus 로고
    • A Bayesian committee machine
    • Volker Tresp. A Bayesian committee machine. Neural Computation, 12(11):2719-2741, 2000.
    • (2000) Neural Computation , vol.12 , Issue.11 , pp. 2719-2741
    • Tresp, V.1
  • 8
    • 29144453489 scopus 로고    scopus 로고
    • A unifying view of sparse approximate Gaussian process regression
    • Joaquin Quiñonero-Candela and Carl Edward Rasmussen. A unifying view of sparse approximate Gaussian process regression. Journal of Machine Learning Research, 6(12):1939-1959, 2005. (Pubitemid 41798128)
    • (2005) Journal of Machine Learning Research , vol.6 , pp. 1939-1959
    • Quinonero-Candela, J.1    Rasmussen, C.E.2
  • 13
    • 33745987673 scopus 로고    scopus 로고
    • Fast forward selection to speed up sparse Gaussian process regression
    • Society for Artificial Intelligence and Statistics
    • Matthias Seeger, Christopher Williams, and Neil Lawrence. Fast forward selection to speed up sparse Gaussian process regression. In Proceedings of the 9th International Workshop on AI Stats. Society for Artificial Intelligence and Statistics, 2003.
    • (2003) Proceedings of the 9th International Workshop on AI Stats
    • Seeger, M.1    Williams, C.2    Lawrence, N.3
  • 15
    • 0001224048 scopus 로고    scopus 로고
    • Sparse bayesian learning and the relevance vector machine
    • DOI 10.1162/15324430152748236
    • Michael E. Tipping. Sparse Bayesian learning and the relevance vector machine. Journal of Machine Learning Research, 1:211-244, 2001. (Pubitemid 33687203)
    • (2001) Journal of Machine Learning Research , vol.1 , Issue.3 , pp. 211-244
    • Tipping, M.E.1
  • 16


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.