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MICAI
2009
Springer
16 years 1 months ago
A Two-Stage Relational Reinforcement Learning with Continuous Actions for Real Service Robots
Reinforcement Learning is a commonly used technique in robotics, however, traditional algorithms are unable to handle large amounts of data coming from the robot’s sensors, requi...
Julio H. Zaragoza, Eduardo F. Morales
PKDD
2009
Springer
95views Data Mining» more  PKDD 2009»
16 years 1 months ago
Non-redundant Subgroup Discovery Using a Closure System
Subgroup discovery is a local pattern discovery task, in which descriptions of subpopulations of a database are evaluated against some quality function. As standard quality functio...
Mario Boley, Henrik Grosskreutz
PKDD
2009
Springer
152views Data Mining» more  PKDD 2009»
16 years 1 months ago
Feature Selection for Value Function Approximation Using Bayesian Model Selection
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...
Tobias Jung, Peter Stone
PKDD
2009
Springer
88views Data Mining» more  PKDD 2009»
16 years 1 months ago
Feature Weighting Using Margin and Radius Based Error Bound Optimization in SVMs
The Support Vector Machine error bound is a function of the margin and radius. Standard SVM algorithms maximize the margin within a given feature space, therefore the radius is fi...
Huyen Do, Alexandros Kalousis, Melanie Hilario
PKDD
2009
Springer
137views Data Mining» more  PKDD 2009»
16 years 1 months ago
On Subgroup Discovery in Numerical Domains
Subgroup discovery is a Knowledge Discovery task that aims at finding subgroups of a population with high generality and distributional unusualness. While several subgroup discove...
Henrik Grosskreutz, Stefan Rüping
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