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» Probabilistic Inference for Fast Learning in Control
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EWRL
2008
13 years 6 months ago
Probabilistic Inference for Fast Learning in Control
Carl Edward Rasmussen, Marc Peter Deisenroth
AAAI
2011
12 years 4 months ago
Coarse-to-Fine Inference and Learning for First-Order Probabilistic Models
Coarse-to-fine approaches use sequences of increasingly fine approximations to control the complexity of inference and learning. These techniques are often used in NLP and visio...
Chloe Kiddon, Pedro Domingos
CIMCA
2005
IEEE
13 years 10 months ago
Statistical Learning Procedure in Loopy Belief Propagation for Probabilistic Image Processing
We give a fast and practical algorithm for statistical learning hyperparameters from observable data in probabilistic image processing, which is based on Gaussian graphical model ...
Kazuyuki Tanaka
CVPR
2008
IEEE
14 years 6 months ago
Sparse probabilistic regression for activity-independent human pose inference
Discriminative approaches to human pose inference involve mapping visual observations to articulated body configurations. Current probabilistic approaches to learn this mapping ha...
Raquel Urtasun, Trevor Darrell
ICRA
2009
IEEE
147views Robotics» more  ICRA 2009»
13 years 11 months ago
Equipping robot control programs with first-order probabilistic reasoning capabilities
— An autonomous robot system that is to act in a real-world environment is faced with the problem of having to deal with a high degree of both complexity as well as uncertainty. ...
Dominik Jain, Lorenz Mösenlechner, Michael Be...