582 search results - page 11 / 117 » Gaussian Processes in Reinforcement Learning |
ICML
2005
IEEE
14 years 10 months ago
2005
IEEE
In this paper, we propose a probabilistic kernel approach to preference learning based on Gaussian processes. A new likelihood function is proposed to capture the preference relat...
NIPS
2008
13 years 11 months ago
2008
The inverse dynamics problem for a robotic manipulator is to compute the torques needed at the joints to drive it along a given trajectory; it is beneficial to be able to learn th...
NIPS
2007
13 years 11 months ago
2007
We show how to use unlabeled data and a deep belief net (DBN) to learn a good covariance kernel for a Gaussian process. We first learn a deep generative model of the unlabeled da...
ICANN
2011
Springer
13 years 1 months ago
2011
Springer
This paper is concerned with estimation of learning curves for Gaussian process regression with multidimensional numerical integration. We propose an approach where the recursion e...
NIPS
2004
13 years 11 months ago
2004
Log-concavity is an important property in the context of optimization, Laplace approximation, and sampling; Bayesian methods based on Gaussian process priors have become quite pop...