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» Modular Neural Networks Evolved by Genetic Programming
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GECCO
2005
Springer
155views Optimization» more  GECCO 2005»
15 years 3 months ago
Co-evolving recurrent neurons learn deep memory POMDPs
Recurrent neural networks are theoretically capable of learning complex temporal sequences, but training them through gradient-descent is too slow and unstable for practical use i...
Faustino J. Gomez, Jürgen Schmidhuber
76
Voted
GECCO
2009
Springer
150views Optimization» more  GECCO 2009»
15 years 4 months ago
Discrete dynamical genetic programming in XCS
A number of representation schemes have been presented for use within Learning Classifier Systems, ranging from binary encodings to neural networks. This paper presents results fr...
Richard Preen, Larry Bull
87
Voted
BIODATAMINING
2008
147views more  BIODATAMINING 2008»
14 years 9 months ago
Neural networks for genetic epidemiology: past, present, and future
During the past two decades, the field of human genetics has experienced an information explosion. The completion of the human genome project and the development of high throughpu...
Alison A. Motsinger-Reif, Marylyn D. Ritchie
ESWA
2006
154views more  ESWA 2006»
14 years 9 months ago
Artificial neural networks with evolutionary instance selection for financial forecasting
In this paper, I propose a genetic algorithm (GA) approach to instance selection in artificial neural networks (ANNs) for financial data mining. ANN has preeminent learning abilit...
Kyoung-jae Kim
EVOW
2006
Springer
15 years 1 months ago
Continuous-Time Recurrent Neural Networks for Generative and Interactive Musical Performance
This paper describes an ongoing exploration into the use of Continuous-Time Recurrent Neural Networks (CTRNNs) as generative and interactive performance tools, and using Genetic Al...
Oliver Bown, Sebastian Lexer