164 search results - page 5 / 33 » Heteroscedastic Gaussian process regression |
117
Voted
JMLR
2010
14 years 10 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...
121
Voted
NIPS
2008
15 years 5 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...
170
Voted
ESSMAC
2003
Springer
15 years 8 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...
111
Voted
NIPS
2003
15 years 5 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...
169
Voted
BMCBI
2011
14 years 7 months ago
2011
Background: The analysis of gene expression from time series underpins many biological studies. Two basic forms of analysis recur for data of this type: removing inactive (quiet) ...