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» Learning for Evolutionary Design
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PLDI
2003
ACM
14 years 3 months ago
Meta optimization: improving compiler heuristics with machine learning
Compiler writers have crafted many heuristics over the years to approximately solve NP-hard problems efficiently. Finding a heuristic that performs well on a broad range of applic...
Mark Stephenson, Saman P. Amarasinghe, Martin C. M...
ECAL
2005
Springer
14 years 3 months ago
A Self-organising, Self-adaptable Cellular System
Abstract. Inspired by the recent advances in evolutionary biology, we have developed a self-organising, self-adaptable cellular system for multitask learning. The main aim of our p...
Lucien Epiney, Mariusz Nowostawski
IJON
2006
161views more  IJON 2006»
13 years 10 months ago
Evolving hybrid ensembles of learning machines for better generalisation
Ensembles of learning machines have been formally and empirically shown to outperform (generalise better than) single predictors in many cases. Evidence suggests that ensembles ge...
Arjun Chandra, Xin Yao
NCA
2007
IEEE
13 years 9 months ago
Using evolution to improve neural network learning: pitfalls and solutions
: Autonomous neural network systems typically require fast learning and good generalization performance, and there is potentially a trade-off between the two. The use of evolutiona...
John A. Bullinaria
CEC
2008
IEEE
14 years 4 months ago
Neuro-evolving maintain-station behavior for realistically simulated boats
— We evolve a neural network controller for a boat that learns to maintain a given bearing and range with respect to a moving target in the Lagoon 3D game environment. Simulating...
Nathan A. Penrod, David Carr, Sushil J. Louis, Bob...