176 search results - page 19 / 36 » Optimal Sample Selection for Batch-mode Reinforcement Learni... |
NIPS
2008
13 years 10 months ago
2008
Policy gradient (PG) reinforcement learning algorithms have strong (local) convergence guarantees, but their learning performance is typically limited by a large variance in the e...
PKDD
2009
Springer
14 years 3 months ago
2009
Springer
Abstract. This paper presents a novel feature selection method for classification of high dimensional data, such as those produced by microarrays. It includes a partial supervisio...
IJCAI
2007
13 years 10 months ago
2007
A key problem in reinforcement learning is finding a good balance between the need to explore the environment and the need to gain rewards by exploiting existing knowledge. Much ...
FOIKS
2008
Springer
14 years 6 months ago
2008
Springer
Supervised learning deals with the inference of a distribution over an output or label space $\CY$ conditioned on points in an observation space $\CX$, given a training dataset $D$...
COLT
2008
Springer
13 years 10 months ago
2008
Springer
The problem of how a teacher and a learner can cooperate in the process of learning concepts from examples in order to minimize the required sample size without “coding tricks...