109 search results - page 7 / 22 » Using Kernel Basis with Relevance Vector Machine for Feature... |
PKDD
2009
Springer
14 years 3 months ago
2009
Springer
Abstract. Feature selection in reinforcement learning (RL), i.e. choosing basis functions such that useful approximations of the unkown value function can be obtained, is one of th...
JMLR
2008
13 years 8 months ago
2008
Ensemble learning algorithms such as boosting can achieve better performance by averaging over the predictions of some base hypotheses. Nevertheless, most existing algorithms are ...
CORR
2006
Springer
13 years 8 months ago
2006
Springer
Abstract. Support Vector Machines (SVMs) are well-established Machine Learning (ML) algorithms. They rely on the fact that i) linear learning can be formalized as a well-posed opti...
ICAI
2009
13 years 6 months ago
2009
- We address the issues of improving the feature generation methods for the value-function approximation and the state space approximation. We focus the improvement of feature gene...
PKDD
2009
Springer
14 years 3 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¬...