C. Rasmussen and Z. Ghahramani. Infinite mixtures of Gaussian process experts. In Advances in Neural Information Processing Systems 14. Home/Search Document Details and Download
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....kernel learning is a subject of current interest. This can be achieved by numerical approximations to matrix inversion [10] and suboptimal projections onto finite subspaces of basis functions without having an explicit parametric form of such basis functions [11, 12] Using mixtures of GPs [13, 14] to make the kernel function input dependent is also a promising technique. None of the Bayesian methods can currently compete in terms of speed with the efficient SVM optimization schemes that have been developed, see e.g. 3] The rest of the paper is organized as follows: In section 2 we ....
Carl E. Rasmussen and Zoubin Ghahramani, "Infinite mixtures of gaussian process experts," in Advances in Neural Information Processing Systems, 2002, number 14.
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C. E. Rasmussen and Z. Ghahramani. Infinite mixtures of Gaussian process experts. In T. G. Dietterich, S. Becker, and Z. Ghahramani, editors, Advances in Neural Information Processing Systems 14, pages 881--888, 2002.
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C. E. Rasmussen and Z. Ghahramani. Infinite mixtures of gaussian process experts. In Advances in Neural Information Processing Systems 14, 2002.
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Carl E. Rasmussen and Zoubin Ghahramani, "Infinite mixtures of gaussian process experts," in Advances in Neural Information Processing Systems, 2002, number 14.
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C.E. Rasmussen and Z. Ghahramani. Infinite mixtures of Gaussian process experts. In T. G. Dietterich, S. Becker, and Z. Ghahramani, editors, Advances in Neural Information Processing Systems 14, Cambridge, Massachusetts, 2002. MIT Press.
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C. Rasmussen and Z. Ghahramani. Infinite mixtures of Gaussian process experts. In Advances in Neural Information Processing Systems 14.
Hierarchical Topic Models and the Nested Chinese.. - Blei, Griffiths.. (2003) (5 citations) (Correct)
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C. Rasmussen and Z. Ghahramani. Infinite mixtures of Gaussian process experts. In Advances in Neural Information Processing Systems 14.
Nonstationary Covariance Functions for Gaussian Process.. - Paciorek, Schervish (2003) (Correct)
No context found.
C.E. Rasmussen and Z. Ghahramani. Infinite mixtures of Gaussian process experts. In T. G. Dietterich, S. Becker, and Z. Ghahramani, editors, Advances in Neural Information Processing Systems 14, Cambridge, Massachusetts, 2002. MIT Press.
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