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106
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ICANN
2010
Springer
15 years 1 months ago
Exploring Continuous Action Spaces with Diffusion Trees for Reinforcement Learning
We propose a new approach for reinforcement learning in problems with continuous actions. Actions are sampled by means of a diffusion tree, which generates samples in the continuou...
Christian Vollmer, Erik Schaffernicht, Horst-Micha...
96
Voted
ICALT
2003
IEEE
15 years 6 months ago
Gaining Computational Literacy by Creating Hybrid Aesthetic Learning Spaces
Although the technical skills of pupils are quite high, the current approach to gain media literacy still focusses on updating software applying skills, rather than exploring the ...
Daniela Reimann, Michael Herczeg, Thomas Winkler, ...
123
Voted
NIPS
2008
15 years 2 months ago
Exploring Large Feature Spaces with Hierarchical Multiple Kernel Learning
For supervised and unsupervised learning, positive definite kernels allow to use large and potentially infinite dimensional feature spaces with a computational cost that only depe...
Francis Bach
CVPR
2012
IEEE
13 years 3 months ago
Learning 3D object templates by hierarchical quantization of geometry and appearance spaces
This paper presents a method for learning 3D object templates from view labeled object images. The 3D template is defined in a joint appearance and geometry space, and is compose...
Wenze Hu
94
Voted
AAAI
1994
15 years 2 months ago
High Dimension Action Spaces in Robot Skill Learning
Table lookup with interpolation is used for many learning and adaptation tasks. Redundant mappings capture the important concept of \motor skill," which is important in real,...
Jeff G. Schneider