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» An Adaptive Supersampling Method
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GECCO
2009
Springer
162views Optimization» more  GECCO 2009»
13 years 6 months ago
Uncertainty handling CMA-ES for reinforcement learning
The covariance matrix adaptation evolution strategy (CMAES) has proven to be a powerful method for reinforcement learning (RL). Recently, the CMA-ES has been augmented with an ada...
Verena Heidrich-Meisner, Christian Igel
ARTCOM
2009
IEEE
13 years 6 months ago
Adaptive Encoding Algorithm for Multispectral Images
A new adaptive multispectral image compression technique based on the regions identified is proposed. The algorithm is adaptive in the sense that according to the data type class ...
Deepa Sankarapandi
ESANN
2008
13 years 10 months ago
Similarities and differences between policy gradient methods and evolution strategies
Natural policy gradient methods and the covariance matrix adaptation evolution strategy, two variable metric methods proposed for solving reinforcement learning tasks, are contrast...
Verena Heidrich-Meisner, Christian Igel
EWRL
2008
13 years 10 months ago
Variable Metric Reinforcement Learning Methods Applied to the Noisy Mountain Car Problem
Two variable metric reinforcement learning methods, the natural actor-critic algorithm and the covariance matrix adaptation evolution strategy, are compared on a conceptual level a...
Verena Heidrich-Meisner, Christian Igel
VVS
1995
IEEE
175views Visualization» more  VVS 1995»
14 years 10 days ago
A Lipschitz Method for Accelerated Volume Rendering
Interpolating discrete volume data into a continuous form adapts implicit surface techniques for rendering volumetric iso-surfaces. One such algorithm uses the Lipschitz condition...
Barton T. Stander, John C. Hart