203 search results - page 15 / 41 » Hierarchical Gaussian Process Regression |
ICANN
2011
Springer
12 years 11 months ago
2011
Springer
Abstract. In many supervised learning tasks it can be costly or infeasible to obtain objective, reliable labels. We may, however, be able to obtain a large number of subjective, po...
Book
"Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning...
ICASSP
2010
IEEE
13 years 7 months ago
2010
IEEE
Gaussian mixture models (GMMs) are a convenient and essential tool for the estimation of probability density functions. Although GMMs are used in many research domains from image ...
ICML
2005
IEEE
14 years 8 months ago
2005
IEEE
We consider the problem of multi-task learning, that is, learning multiple related functions. Our approach is based on a hierarchical Bayesian framework, that exploits the equival...
DSMML
2004
Springer
14 years 1 months ago
2004
Springer
The informative vector machine (IVM) is a practical method for Gaussian process regression and classification. The IVM produces a sparse approximation to a Gaussian process by com...