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» Evolving Complex Neural Networks
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STOC
1993
ACM
141views Algorithms» more  STOC 1993»
15 years 1 months ago
Bounds for the computational power and learning complexity of analog neural nets
Abstract. It is shown that high-order feedforward neural nets of constant depth with piecewisepolynomial activation functions and arbitrary real weights can be simulated for Boolea...
Wolfgang Maass
ESANN
2001
14 years 11 months ago
Some known facts about financial data
: Many researchers are interesting in applying the neural networks methods to financial data. In fact these data are very complex, and classical methods do not always give satisfac...
Eric de Bodt, Joseph Rynkiewicz, Marie Cottrell
AE
2001
Springer
15 years 2 months ago
Evolving Objects: A General Purpose Evolutionary Computation Library
This paper presents the evolving objects library (EOlib), an object-oriented framework for evolutionary computation (EC) that aims to provide a flexible set of classes to build EC...
Maarten Keijzer, Juan J. Merelo Guervós, Gu...
ESANN
2004
14 years 11 months ago
Evolutionary Optimization of Neural Networks for Face Detection
For face recognition from video streams speed and accuracy are vital aspects. The first decision whether a preprocessed image region represents a human face or not is often made by...
Stefan Wiegand, Christian Igel, Uwe Handmann
GECCO
2007
Springer
182views Optimization» more  GECCO 2007»
15 years 4 months ago
Generating large-scale neural networks through discovering geometric regularities
Connectivity patterns in biological brains exhibit many repeating motifs. This repetition mirrors inherent geometric regularities in the physical world. For example, stimuli that ...
Jason Gauci, Kenneth O. Stanley