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IJON
2010
1 years 4 months ago
2010
We present an EM-algorithm for the problem of learning preferences with Gaussian processes in the context of multi-task learning. We validate our approach on an audiological data ...
NIPS
2000
1 years 6 months ago
2000
We introduce the mixture of Gaussian processes (MGP) model which is useful for applications in which the optimal bandwidth of a map is input dependent. The MGP is derived from the...
NIPS
2004
1 years 6 months ago
2004
Gaussian processes are usually parameterised in terms of their covariance functions. However, this makes it difficult to deal with multiple outputs, because ensuring that the cova...
ILP
2003
Springer
1 years 10 months ago
2003
Springer
RRL is a relational reinforcement learning system based on Q-learning in relational state-action spaces. It aims to enable agents to learn how to act in an environment that has no ...
ESSMAC
2003
Springer
1 years 10 months ago
2003
Springer
Abstract. Gaussian process models provide a probabilistic non-parametric modelling approach for black-box identification of nonlinear dynamic systems. The Gaussian processes can h...
ESSMAC
2003
Springer
1 years 10 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...
MCS
2005
Springer
1 years 11 months ago
2005
Springer
This paper describes a unified approach, based on Gaussian Processes, for achieving sensor fusion under the problematic conditions of missing channels and noisy labels. Under the ...
IROS
2007
IEEE
1 years 11 months ago
2007
IEEE
Abstract— We propose to improve the locomotive performance of humanoid robots by using approximated biped stepping and walking dynamics with reinforcement learning (RL). Although...
IROS
2008
IEEE
1 years 12 months ago
2008
IEEE
— High performance and compliant robot control requires accurate dynamics models which cannot be obtained analytically for sufficiently complex robot systems. In such cases, mac...
PKDD
2009
Springer
2 years 2 days ago
2009
Springer
Abstract. Gaussian processes have successfully been used to learn preferences among entities as they provide nonparametric Bayesian approaches for model selection and probabilistic...
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