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GECCO
2010
Springer
168views Optimization» more  GECCO 2010»
14 years 2 months ago
Investigating whether hyperNEAT produces modular neural networks
HyperNEAT represents a class of neuroevolutionary algorithms that captures some of the power of natural development with a ionally efficient high-level abstraction of development....
Jeff Clune, Benjamin E. Beckmann, Philip K. McKinl...
GECCO
2010
Springer
173views Optimization» more  GECCO 2010»
14 years 2 months ago
Evolving the placement and density of neurons in the hyperneat substrate
The Hypercube-based NeuroEvolution of Augmenting Topologies (HyperNEAT) approach demonstrated that the pattern of weights across the connectivity of an artificial neural network ...
Sebastian Risi, Joel Lehman, Kenneth O. Stanley
ICS
2010
Tsinghua U.
14 years 2 months ago
Handling task dependencies under strided and aliased references
The emergence of multicore processors has increased the need for simple parallel programming models usable by nonexperts. The ability to specify subparts of a bigger data structur...
Josep M. Pérez, Rosa M. Badia, Jesús...
ICSE
2010
IEEE-ACM
14 years 2 months ago
From behaviour preservation to behaviour modification: constraint-based mutant generation
The efficacy of mutation analysis depends heavily on its capability to mutate programs in such a way that they remain executable and exhibit deviating behaviour. Whereas the forme...
Friedrich Steimann, Andreas Thies
PPPJ
2009
ACM
14 years 2 months ago
Virtual reuse distance analysis of SPECjvm2008 data locality
Reuse distance analysis has been proved promising in evaluating and predicting data locality for programs written in Fortran or C/C++. But its effect has not been examined for ap...
Xiaoming Gu, Xiao-Feng Li, Buqi Cheng, Eric Huang