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» Variational methods for Reinforcement Learning
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ICML
2006
IEEE
14 years 8 months ago
Nonstationary kernel combination
The power and popularity of kernel methods stem in part from their ability to handle diverse forms of structured inputs, including vectors, graphs and strings. Recently, several m...
Darrin P. Lewis, Tony Jebara, William Stafford Nob...
UAI
2008
13 years 9 months ago
Improving Gradient Estimation by Incorporating Sensor Data
An efficient policy search algorithm should estimate the local gradient of the objective function, with respect to the policy parameters, from as few trials as possible. Whereas m...
Gregory Lawrence, Stuart J. Russell
IVC
2006
120views more  IVC 2006»
13 years 7 months ago
Facial pose from 3D data
The distribution of the apparent 3D shape of human faces across the view-sphere is complex, owing to factors such as variations in identity, facial expression, minor occlusions an...
Ajit Rajwade, Martin D. Levine
JMLR
2010
101views more  JMLR 2010»
13 years 2 months ago
Classification Using Geometric Level Sets
A variational level set method is developed for the supervised classification problem. Nonlinear classifier decision boundaries are obtained by minimizing an energy functional tha...
Kush R. Varshney, Alan S. Willsky
TSP
2010
13 years 2 months ago
Testing stationarity with surrogates: a time-frequency approach
An operational framework is developed for testing stationarity relatively to an observation scale, in both stochastic and deterministic contexts. The proposed method is based on a ...
Pierre Borgnat, Patrick Flandrin, Paul Honeine, C&...