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» Evolution at Learning: How to Promote Generalization
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GECCO
2010
Springer
191views Optimization» more  GECCO 2010»
13 years 11 months ago
Initialization parameter sweep in ATHENA: optimizing neural networks for detecting gene-gene interactions in the presence of sma
Recent advances in genotyping technology have led to the generation of an enormous quantity of genetic data. Traditional methods of statistical analysis have proved insufficient i...
Emily Rose Holzinger, Carrie C. Buchanan, Scott M....
NIPS
2007
13 years 7 months ago
A New View of Automatic Relevance Determination
Automatic relevance determination (ARD) and the closely-related sparse Bayesian learning (SBL) framework are effective tools for pruning large numbers of irrelevant features leadi...
David P. Wipf, Srikantan S. Nagarajan
GECCO
2009
Springer
13 years 10 months ago
NEAT in increasingly non-linear control situations
Evolution of neural networks, as implemented in NEAT, has proven itself successful on a variety of low-level control problems such as pole balancing and vehicle control. Nonethele...
Matthias J. Linhardt, Martin V. Butz
AICOM
2002
103views more  AICOM 2002»
13 years 6 months ago
The emergent computational potential of evolving artificial living systems
The computational potential of artificial living systems can be studied without knowing the algorithms that govern their behavior. Modeling single organisms by means of socalled c...
Jirí Wiedermann, Jan van Leeuwen
ICAI
2008
13 years 7 months ago
Nonrestrictive Concept-Acquisition by Representational Redescription
coarse procedures or very abstract frames from the point of view of algorithm, because some crucial issues like the representation, evolution, storage, and learning process of conc...
Hui Wei, Yan Chen