176 search results - page 9 / 36 » Optimal Sample Selection for Batch-mode Reinforcement Learni... |
NIPS
2001
13 years 9 months ago
2001
Policy gradient methods for reinforcement learning avoid some of the undesirable properties of the value function approaches, such as policy degradation (Baxter and Bartlett, 2001...
ICML
2009
IEEE
14 years 8 months ago
2009
IEEE
We introduce a new algorithm for binary classification in the selective sampling protocol. Our algorithm uses Regularized Least Squares (RLS) as base classifier, and for this reas...
ECIR
2009
Springer
14 years 4 months ago
2009
Springer
Abstract. Learning ranking functions is crucial for solving many problems, ranging from document retrieval to building recommendation systems based on an individual user’s prefer...
PKDD
2009
Springer
14 years 7 days ago
2009
Springer
Abstract. This paper focuses on Active Learning with a limited number of queries; in application domains such as Numerical Engineering, the size of the training set might be limite...
ICML
2003
IEEE
14 years 8 months ago
2003
IEEE
The paper explores a very simple agent design method called Q-decomposition, wherein a complex agent is built from simpler subagents. Each subagent has its own reward function and...