Sparse greedy Gaussian process regression

Advances in Neural Information Processing Systems

Volumn , Issue , 2001, Pages

  Smola, Alex J ^a   Bartlett, Peter ^a  

^a AUSTRALIAN NATIONAL UNIVERSITY   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

GAUSSIAN DISTRIBUTION; GAUSSIAN NOISE (ELECTRONIC);

APPROXIMATION ERRORS; COMPUTATIONAL REQUIREMENTS; CONFIDENCE BOUNDS; GAUSSIAN PROCESS REGRESSION; GAUSSIAN PROCESSES; LARGE-SCALE PROBLEM; MAXIMUM A POSTERIORI ESTIMATES; SCALING BEHAVIOURS;

COST BENEFIT ANALYSIS;

EID: 84899000575     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (8)

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7. A.J. Smola and B. Schölkopf. Sparse greedy matrix approximation for machine learning. In P. Langley, editor, Proceedings of the 17th International Conference on Machine Learning, pages 911-918, San Francisco, 2000. Morgan Kaufman.
8. C.K.I. Williams and M. Seeger. The effect of the input density distribution on kernel-based classifiers. In P. Langley, editor, Proceedings of the Seventeenth International Conference on Machine Learning, pages 1159-1166, San Francisco, California, 2000. Morgan Kaufmann.