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ICML
2006
IEEE
14 years 10 months ago
Kernel Predictive Linear Gaussian models for nonlinear stochastic dynamical systems
The recent Predictive Linear Gaussian model (or PLG) improves upon traditional linear dynamical system models by using a predictive representation of state, which makes consistent...
David Wingate, Satinder P. Singh
ICANN
2003
Springer
14 years 3 months ago
Unsupervised Learning of a Kinematic Arm Model
Abstract. An abstract recurrent neural network trained by an unsupervised method is applied to the kinematic control of a robot arm. The network is a novel extension of the Neural ...
Heiko Hoffmann, Ralf Möller
GECCO
2006
Springer
168views Optimization» more  GECCO 2006»
14 years 1 months ago
A Bayesian approach to learning classifier systems in uncertain environments
In this paper we propose a Bayesian framework for XCS [9], called BXCS. Following [4], we use probability distributions to represent the uncertainty over the classifier estimates ...
Davide Aliprandi, Alex Mancastroppa, Matteo Matteu...
ESANN
2004
13 years 11 months ago
Learning by geometrical shape changes of dendritic spines
The role of dendritic spines in neuronal information processing is still not completely clear. However, it is known that spines can change shape rapidly during development and duri...
Andreas Herzog, Vadym Spravedlyvyy, Karsten Kube, ...
ESANN
2003
13 years 11 months ago
Neural networks organizations to learn complex robotic functions
Abstract. This paper considers the general problem of function estimation with a modular approach of neural computing. We propose to use functionally independent subnetworks to lea...
Gilles Hermann, Patrice Wira, Jean-Philippe Urban