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Volumn 30, Issue 4, 2013, Pages 98-111

Kernel embeddings of conditional distributions: A unified kernel framework for nonparametric inference in graphical models

Author keywords

[No Author keywords available]

Indexed keywords

GRAPHIC METHODS; LEARNING SYSTEMS; STATISTICAL METHODS;

EID: 85032751252     PISSN: 10535888     EISSN: None     Source Type: Journal    
DOI: 10.1109/MSP.2013.2252713     Document Type: Review
Times cited : (267)

References (29)
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    • K. Fukumizu, F. R. Bach, and M. I. Jordan, "Dimensionality reduction for supervised learning with reproducing kernel Hilbert spaces, " J. Mach. Learn. Res., vol. 5, pp. 73-99, 2004.
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  • 22
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    • S. K. Zhou and R. Chellappa, "From sample similarity to ensemble similarity: Probabilistic distance measures in reproducing kernel Hilbert space, " IEEE Trans. Pattern Anal. Mach. Intell., vol. 28, no. 6, pp. 917-929, 2006.
    • (2006) IEEE Trans. Pattern Anal. Mach. Intell. , vol.28 , Issue.6 , pp. 917-929
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  • 23
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  • 27
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    • C. Andrieu, N. de Freitas, A. Doucet, and M. I. Jordan, "An introduction to MCMC for machine learning, " Mach. Learn., vol. 50, no. 1-2, pp. 5-43, 2003.
    • (2003) Mach. Learn. , vol.50 , Issue.1-2 , pp. 5-43
    • Andrieu, C.1    De Freitas, N.2    Doucet, A.3    Jordan, M.I.4
  • 28
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    • Make3d: Learning 3d scene structure from a single still image
    • A. Saxena, M. Sun, and A. Y. Ng, "Make3d: Learning 3d scene structure from a single still image, " IEEE Trans. Pattern Anal. Mach. Intell., vol. 31, no. 5, pp. 824-840, 2009.
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    • New extension of the Kalman filter to nonlinear systems
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.