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ECML
2005
Springer
15 years 8 months ago
Active Learning in Partially Observable Markov Decision Processes
This paper examines the problem of finding an optimal policy for a Partially Observable Markov Decision Process (POMDP) when the model is not known or is only poorly specified. W...
Robin Jaulmes, Joelle Pineau, Doina Precup
IJCNN
2000
IEEE
15 years 7 months ago
An Incremental Growing Neural Network and its Application to Robot Control
This paper describes a novel network model, which is able to control its growth on the basis of the approximation requests. Two classes of self-tuning neural models are considered...
A. Carlevarino, R. Martinotti, Giorgio Metta, Giul...
124
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ICANN
2007
Springer
15 years 6 months ago
The Role of Internal Oscillators for the One-Shot Learning of Complex Temporal Sequences
We present an artificial neural network used to learn online complex temporal sequences of gestures to a robot. The system is based on a simple temporal sequences learning architec...
Matthieu Lagarde, Pierre Andry, Philippe Gaussier
CORR
2011
Springer
213views Education» more  CORR 2011»
14 years 10 months ago
Adapting to Non-stationarity with Growing Expert Ensembles
Forecasting sequences by expert ensembles generally assumes stationary or near-stationary processes; however, in complex systems and many real-world applications, we are frequentl...
Cosma Rohilla Shalizi, Abigail Z. Jacobs, Aaron Cl...
CVPR
2008
IEEE
16 years 4 months ago
Shading models for illumination and reflectance invariant shape detectors
Many objects have smooth surfaces of a fairly uniform color, thereby exhibiting shading patterns that reveal information about its shape, an important clue to the nature of the ob...
Peter Nillius, Josephine Sullivan, Antonis A. Argy...