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TNN
2008
138views more  TNN 2008»
14 years 11 months ago
A Fast and Scalable Recurrent Neural Network Based on Stochastic Meta Descent
This brief presents an efficient and scalable online learning algorithm for recurrent neural networks (RNNs). The approach is based on the real-time recurrent learning (RTRL) algor...
Zhenzhen Liu, Itamar Elhanany
IJON
2006
91views more  IJON 2006»
14 years 11 months ago
Symmetry axis extraction by a neural network
This paper proposes a neural network model that extracts axes of symmetry from visual patterns. The input patterns can be line drawings, plane figures or gray-scaled natural image...
Kunihiko Fukushima, Masayuki Kikuchi
ROBOCUP
2004
Springer
138views Robotics» more  ROBOCUP 2004»
15 years 5 months ago
An Algorithm That Recognizes and Reproduces Distinct Types of Humanoid Motion Based on Periodically-Constrained Nonlinear PCA
Abstract. This paper proposes a new algorithm for the automatic segmentation of motion data from a humanoid soccer playing robot that allows feedforward neural networks to generali...
Rawichote Chalodhorn, Karl F. MacDorman, Minoru As...
GECCO
2006
Springer
167views Optimization» more  GECCO 2006»
15 years 3 months ago
Genomic computing networks learn complex POMDPs
A genomic computing network is a variant of a neural network for which a genome encodes all aspects, both structural and functional, of the network. The genome is evolved by a gen...
David J. Montana, Eric Van Wyk, Marshall Brinn, Jo...
IJCNN
2008
IEEE
15 years 6 months ago
Building meta-learning algorithms basing on search controlled by machine complexity
Abstract— Meta-learning helps us find solutions to computational intelligence (CI) challenges in automated way. Metalearning algorithm presented in this paper is universal and m...
Norbert Jankowski, Krzysztof Grabczewski