582 search results - page 8 / 117 » Reinforcement learning with Gaussian processes |
ECML
2006
Springer
14 years 2 months ago
2006
Springer
Abstract. In contrast to the standard inductive inference setting of predictive machine learning, in real world learning problems often the test instances are already available at ...
ICML
2008
IEEE
14 years 11 months ago
2008
IEEE
Point processes are difficult to analyze because they provide only a sparse and noisy observation of the intensity function driving the process. Gaussian Processes offer an attrac...
PKDD
2010
Springer
13 years 9 months ago
2010
Springer
Abstract. In preference learning, the algorithm observes pairwise relative judgments (preference) between items as training data for learning an ordering of all items. This is an i...
NIPS
2007
14 years 8 days ago
2007
In this paper we model relational random variables on the edges of a network using Gaussian processes (GPs). We describe appropriate GP priors, i.e., covariance functions, for dir...
ICANN
2010
Springer
13 years 12 months ago
2010
Springer
Abstract. In this paper we present a Reinforcement Learning (RL) approach with the capability to train neural adaptive controllers for complex control problems without expensive on...