112 search results - page 2 / 23 » Gaussian Processes for Machine Learning (GPML) Toolbox |
KDD
2007
ACM
14 years 5 months ago
2007
ACM
A wide variety of machine learning problems can be described as minimizing a regularized risk functional, with different algorithms using different notions of risk and different r...
Book
"Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning...
AC
2003
Springer
13 years 10 months ago
2003
Springer
ICML
2005
IEEE
14 years 6 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...
ICML
2003
IEEE
14 years 6 months ago
2003
IEEE
We present a novel Bayesian approach to the problem of value function estimation in continuous state spaces. We define a probabilistic generative model for the value function by i...