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GECCO
2005
Springer
196views Optimization» more  GECCO 2005»
15 years 10 months ago
Providing information from the environment for growing electronic circuits through polymorphic gates
This paper deals with the evolutionary design of programs (constructors) that are able to create (n+2)-input circuits from n-input circuits. The growing circuits are composed of p...
Michal Bidlo, Lukás Sekanina
GECCO
2005
Springer
119views Optimization» more  GECCO 2005»
15 years 10 months ago
A new evolutionary method for time series forecasting
This paper presents a new method — the Time-delay Added Evolutionary Forecasting (TAEF) method — for time series prediction which performs an evolutionary search of the minimu...
Tiago A. E. Ferreira, Germano C. Vasconcelos, Paul...
GECCO
2005
Springer
132views Optimization» more  GECCO 2005»
15 years 10 months ago
A statistical learning theory approach of bloat
Code bloat, the excessive increase of code size, is an important issue in Genetic Programming (GP). This paper proposes a theoretical analysis of code bloat in the framework of sy...
Sylvain Gelly, Olivier Teytaud, Nicolas Bredeche, ...
GECCO
2005
Springer
155views Optimization» more  GECCO 2005»
15 years 10 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
GECCO
2005
Springer
158views Optimization» more  GECCO 2005»
15 years 10 months ago
Applying both positive and negative selection to supervised learning for anomaly detection
This paper presents a novel approach of applying both positive selection and negative selection to supervised learning for anomaly detection. It first learns the patterns of the n...
Xiaoshu Hang, Honghua Dai