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GECCO
2007
Springer
212views Optimization» more  GECCO 2007»
14 years 27 days ago
A developmental model of neural computation using cartesian genetic programming
The brain has long been seen as a powerful analogy from which novel computational techniques could be devised. However, most artificial neural network approaches have ignored the...
Gul Muhammad Khan, Julian F. Miller, David M. Hall...
IJCNN
2006
IEEE
14 years 23 days ago
Reservoir-based techniques for speech recognition
— A solution for the slow convergence of most learning rules for Recurrent Neural Networks (RNN) has been proposed under the terms Liquid State Machines (LSM) and Echo State Netw...
David Verstraeten, Benjamin Schrauwen, Dirk Stroob...
ICANN
2009
Springer
13 years 11 months ago
Constrained Learning Vector Quantization or Relaxed k-Separability
Neural networks and other sophisticated machine learning algorithms frequently miss simple solutions that can be discovered by a more constrained learning methods. Transition from ...
Marek Grochowski, Wlodzislaw Duch
PPSN
2004
Springer
14 years 2 days ago
Coupling of Evolution and Learning to Optimize a Hierarchical Object Recognition Model
Abstract. A key problem in designing artificial neural networks for visual object recognition tasks is the proper choice of the network architecture. Evolutionary optimization met...
Georg Schneider, Heiko Wersing, Bernhard Sendhoff,...
ICRA
2009
IEEE
137views Robotics» more  ICRA 2009»
14 years 1 months ago
Continuous vocal imitation with self-organized vowel spaces in Recurrent Neural Network
Abstract— A continuous vocal imitation system was developed using a computational model that explains the process of phoneme acquisition by infants. Human infants perceive speech...
Hisashi Kanda, Tetsuya Ogata, Toru Takahashi, Kazu...