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Volumn 30, Issue 1, 2011, Pages 3-23

Learning GP-BayesFilters via Gaussian process latent variable models

Author keywords

Bayesian filtering; Gaussian process; Machine learning; System control; System identification; Time alignment

Indexed keywords

BAYESIAN FILTERING; GAUSSIAN PROCESSES; MACHINE LEARNING; SYSTEM CONTROL; SYSTEM IDENTIFICATION; TIME ALIGNMENT;

EID: 79951555580     PISSN: 09295593     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10514-010-9213-0     Document Type: Conference Paper
Times cited : (70)

References (39)
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  • 13
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    • Kawahara, Y., Yairi, T., & Machida, K. (2007). A kernel subspace method by stochastic realization for learning nonlinear dynamical systems. In B. Schölkopf, J. Platt, & T. Hoffman (Eds.), Advances in neural information processing systems (Vol. 19, pp. 665-672). Cambridge: MIT Press.
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    • Ko, J., & Fox, D. (2009). Learning GP-Bayesfilters via Gaussian process latent variable models. In Proc. of robotics: science and systems, RSS.
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    • Ko, J.1    Fox, D.2
  • 20
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    • Lawrence, N.1
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    • C. D. Meyer (eds). Society for Industrial and Applied Mathematics Philadelphia 0962.15001
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.