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GECCO 2012: Call for Papers on GENETICS-BASED MACHINE LEARNING (GBML)
2012 Genetic and Evolutionary Computation Conference (GECCO-2012)
July 7-11, Philadelphia, USA
http://www.sigevo.org/gecco-2012/
Submission deadline: January 13, 2012
Co-located with the International Workshop on Learning Classifier Systems (IWLCS)
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The Genetics-Based Machine Learning (GBML) track at GECCO covers all
advances in theory and application of evolutionary computation methods
to Machine Learning (ML) problems.
ML presents an array of paradigms -- unsupervised, semi-supervised,
supervised, and reinforcement learning -- which frame a wide range of
clustering, classification, regression, prediction and control tasks.
Evolutionary methods have a range of uses in ML:
- addressing subproblems of ML e.g.
- feature selection and construction
- optimising parameters of other ML methods
- as learning methods e.g.
- generating classification hypotheses with Genetic Programming
- learning control systems or cognitive modelling with Learning Classifier Systems
- as meta-learners which adapt base learners e.g.
- evolving the structure and weights of neural networks
- evolving the data base and rule base in genetic fuzzy systems
- evolving ensembles of base learners
- evolving representations, update rules or algorithms for base
learners
The global search performed by evolutionary methods can complement the
local search of non-evolutionary methods and combinations of the two
are particularly welcome.
Free tutorials include:
- Learning Classifier Systems
- Large Scale Data Mining using Genetics-Based Machine Learning
Track Chairs
Dr. Will Browne, Victoria University of Wellington, NZ (will.browne -at- ecs -dot- vuw -dot- ac -dot- nz)
Dr. Tim Kovacs, University of Bristol, U.K. (kovacs -at- cs -dot- bris -dot- ac -dot- uk)
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