340 search results - page 24 / 68 » Kernelized value function approximation for reinforcement le... |
104
Voted
ICML
1999
IEEE
16 years 3 months ago
1999
IEEE
: Numerical function approximation over a Boolean domain is a classical problem with wide application to data modeling tasks and various forms of learning. A great many function ap...
148
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ICML
2007
IEEE
16 years 3 months ago
2007
IEEE
Regularized Kernel Discriminant Analysis (RKDA) performs linear discriminant analysis in the feature space via the kernel trick. The performance of RKDA depends on the selection o...
110
Voted
PKDD
2009
Springer
15 years 9 months ago
2009
Springer
Abstract. Innovations such as optimistic exploration, function approximation, and hierarchical decomposition have helped scale reinforcement learning to more complex environments, ...
144
Voted
ECML
2005
Springer
15 years 8 months ago
2005
Springer
This paper investigates a novel model-free reinforcement learning architecture, the Natural Actor-Critic. The actor updates are based on stochastic policy gradients employing Amari...
ICASSP
2010
IEEE
15 years 2 months ago
2010
IEEE
The sequence kernel has been shown to be a promising kernel function for learning from sequential data such as speech and DNA. However, it is not scalable to massive datasets due ...