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GECCO
2007
Springer
175views Optimization» more  GECCO 2007»
16 years 25 days ago
An evolutionary multiobjective approach to design highly non-linear Boolean functions
The proliferation of all kinds of devices with different security requirements and constraints, and the arms-race nature of the security problem are increasingly demanding the de...
Hernán E. Aguirre, Hiroyuki Okazaki, Yasush...
ICIP
2009
IEEE
16 years 7 months ago
Optimum Kernel Function Design From Scale Space Features For Object Detection
Scale-space representation of an image is a significant way to generate features for classification. However, for a specific classification task, the entire scale-space may not be...
CIKM
2009
Springer
15 years 10 months ago
Empirical justification of the gain and discount function for nDCG
The nDCG measure has proven to be a popular measure of retrieval effectiveness utilizing graded relevance judgments. However, a number of different instantiations of nDCG exist, d...
Evangelos Kanoulas, Javed A. Aslam
GECCO
2008
Springer
123views Optimization» more  GECCO 2008»
15 years 7 months ago
Precision, local search and unimodal functions
We investigate the effects of precision on the efficiency of various local search algorithms on 1-D unimodal functions. We present a (1 + 1)-EA with adaptive step size which fin...
Martin Dietzfelbinger, Jonathan E. Rowe, Ingo Wege...
GECCO
2011
Springer
232views Optimization» more  GECCO 2011»
14 years 10 months ago
Mutation rates of the (1+1)-EA on pseudo-boolean functions of bounded epistasis
When the epistasis of the fitness function is bounded by a constant, we show that the expected fitness of an offspring of the (1+1)-EA can be efficiently computed for any point...
Andrew M. Sutton, Darrell Whitley, Adele E. Howe