203 search results - page 5 / 41 » Hierarchical Gaussian Process Regression |
JMLR
2010
13 years 2 months ago
2010
We present a new sparse Gaussian Process (GP) model for regression. The key novel idea is to sparsify the spectral representation of the GP. This leads to a simple, practical algo...
NIPS
2008
13 years 9 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...
ICML
2007
IEEE
14 years 8 months ago
2007
IEEE
This paper presents a novel Gaussian process (GP) approach to regression with inputdependent noise rates. We follow Goldberg et al.'s approach and model the noise variance us...
ESSMAC
2003
Springer
14 years 25 days 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...
NIPS
2003
13 years 9 months ago
2003
We introduce a class of nonstationary covariance functions for Gaussian process (GP) regression. Nonstationary covariance functions allow the model to adapt to functions whose smo...