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ESANN
2008
14 years 11 months ago
Learning Inverse Dynamics: a Comparison
While it is well-known that model can enhance the control performance in terms of precision or energy efficiency, the practical application has often been limited by the complexiti...
Duy Nguyen-Tuong, Jan Peters, Matthias Seeger, Ber...
ICASSP
2011
IEEE
14 years 1 months ago
Arccosine kernels: Acoustic modeling with infinite neural networks
Neural networks are a useful alternative to Gaussian mixture models for acoustic modeling; however, training multilayer networks involves a difficult, nonconvex optimization that...
Chih-Chieh Cheng, Brian Kingsbury
ICIAP
2001
Springer
15 years 9 months ago
Recognition of Shape-Changing Hand Gestures Based on Switching Linear Model
We present a method to track and recognize shape-changing hand gestures simultaneously. The switching linear model using active contour model well corresponds to temporal shapes a...
Mun Ho Jeong, Yoshinori Kuno, Nobutaka Shimada, Yo...
ICRA
2010
IEEE
104views Robotics» more  ICRA 2010»
14 years 8 months ago
Using model knowledge for learning inverse dynamics
— In recent years, learning models from data has become an increasingly interesting tool for robotics, as it allows straightforward and accurate model approximation. However, in ...
Duy Nguyen-Tuong, Jan Peters
UAI
2003
14 years 11 months ago
Bayesian Hierarchical Mixtures of Experts
The Hierarchical Mixture of Experts (HME) is a well-known tree-structured model for regression and classification, based on soft probabilistic splits of the input space. In its o...
Christopher M. Bishop, Markus Svensén