Rasmussen, C. E. Reduced rank Gaussian process learning, 2002. Unpublished Manuscript. Home/Search Document Not in Database Summary Related Articles Check |
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Transductive and Inductive Methods for Approximate Gaussian.. - Schwaighofer (2002) (1 citation) (Correct)
....learning scheme that focuses on a sparse model of the posterior process that arises from combining a Gaussian process prior with a general This method was not developed particularly for GPR, yet we expect this basis selection scheme to be superior to a purely random choice. However, Rasmussen [5] noted that Smola and Bartlett [7] falsely assume that the additive constant terms in the log likelihood remain constant during basis selection. likelihood model of data. The posterior process is assumed to be Gaussian and is modeled by a set of basis vectors. Upon arrival of a new data point, ....
Rasmussen, C. E. Reduced rank Gaussian process learning, 2002. Unpublished Manuscript.
Transductive and Inductive Methods for - Approximate Gaussian Process (Correct)
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Rasmussen, C. E. Reduced rank Gaussian process learning, 2002. Unpublished Manuscript.
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