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GECCO
2009
Springer
14 years 1 days ago
The sensitivity of HyperNEAT to different geometric representations of a problem
HyperNEAT, a generative encoding for evolving artificial neural networks (ANNs), has the unique and powerful ability to exploit the geometry of a problem (e.g., symmetries) by enc...
Jeff Clune, Charles Ofria, Robert T. Pennock
DMIN
2006
126views Data Mining» more  DMIN 2006»
13 years 8 months ago
Comparison and Analysis of Mutation-based Evolutionary Algorithms for ANN Parameters Optimization
Mutation-based Evolutionary Algorithms, also known as Evolutionary Programming (EP) are commonly applied to Artificial Neural Networks (ANN) parameters optimization. This paper pre...
Kristina Davoian, Alexander Reichel, Wolfram-Manfr...
BMCBI
2007
126views more  BMCBI 2007»
13 years 7 months ago
Including probe-level uncertainty in model-based gene expression clustering
Background: Clustering is an important analysis performed on microarray gene expression data since it groups genes which have similar expression patterns and enables the explorati...
Xuejun Liu, Kevin K. Lin, Bogi Andersen, Magnus Ra...
GECCO
2007
Springer
183views Optimization» more  GECCO 2007»
13 years 11 months ago
Evolving distributed agents for managing air traffic
Air traffic management offers an intriguing real world challenge to designing large scale distributed systems using evolutionary computation. The ability to evolve effective air t...
Adrian K. Agogino, Kagan Tumer
PATMOS
2007
Springer
14 years 1 months ago
Optimization for Real-Time Systems with Non-convex Power Versus Speed Models
Abstract. Until now, the great majority of research in low-power systems has assumed a convex power model. However, recently, due to the confluence of emerging technological and ar...
Ani Nahapetian, Foad Dabiri, Miodrag Potkonjak, Ma...