86 search results - page 1 / 18 » Approximation of Gaussian process regression models after tr... |
ESANN
2008
13 years 6 months ago
2008
The evaluation of a standard Gaussian process regression model takes time linear in the number of training data points. In this paper, the models are approximated in the feature sp...
ESSMAC
2003
Springer
13 years 10 months ago
2003
Springer
Abstract. While there is strong motivation for using Gaussian Processes (GPs) due to their excellent performance in regression and classification problems, their computational com...
ECML
2006
Springer
13 years 8 months ago
2006
Springer
Abstract. In contrast to the standard inductive inference setting of predictive machine learning, in real world learning problems often the test instances are already available at ...
NIPS
2008
13 years 6 months ago
2008
Learning in real-time applications, e.g., online approximation of the inverse dynamics model for model-based robot control, requires fast online regression techniques. Inspired by...
DSMML
2004
Springer
13 years 10 months ago
2004
Springer
Learning curves for Gaussian process (GP) regression can be strongly affected by a mismatch between the ‘student’ model and the ‘teacher’ (true data generation process), e...