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PKDD
2009
Springer
15 years 4 months ago
2009
Springer
Abstract. Innovations such as optimistic exploration, function approximation, and hierarchical decomposition have helped scale reinforcement learning to more complex environments, ...
PKDD
2009
Springer
15 years 4 months ago
2009
Springer
We explore an algorithm for training SVMs with Kernels that can represent the learned rule using arbitrary basis vectors, not just the support vectors (SVs) from the training set. ...
PKDD
2009
Springer
15 years 4 months ago
2009
Springer
Structured prediction has become very important in recent years. A simple but notable class of structured prediction is one for sequences, so-called sequential labeling. For sequen...
PKDD
2009
Springer
15 years 4 months 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...
PKDD
2009
Springer
15 years 4 months ago
2009
Springer
A frequent problem in density level-set estimation is the choice of the right features that give rise to compact and concise representations of the observed data. We present an eï¬...