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CVPR
2012
IEEE
13 years 8 months ago
Unsupervised feature learning framework for no-reference image quality assessment
In this paper, we present an efficient general-purpose objective no-reference (NR) image quality assessment (IQA) framework based on unsupervised feature learning. The goal is to...
Peng Ye, Jayant Kumar, Le Kang, David S. Doermann
GECCO
2006
Springer
167views Optimization» more  GECCO 2006»
15 years 10 months ago
Estimating the destructiveness of crossover on binary tree representations
In some cases, evolutionary algorithms represent individuals as typical binary trees with n leaves and n-1 internal nodes. When designing a crossover operator for a particular rep...
Luke Sheneman, James A. Foster
CORR
2007
Springer
165views Education» more  CORR 2007»
15 years 6 months ago
Comparison of Tree-Child Phylogenetic Networks
Abstract—Phylogenetic networks are a generalization of phylogenetic trees that allow for the representation of non-treelike evolutionary events, like recombination, hybridization...
Gabriel Cardona, Francesc Rosselló, Gabriel...
213
Voted
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
GECCO
2007
Springer
183views Optimization» more  GECCO 2007»
16 years 17 days ago
Self-adaptive simulated binary crossover for real-parameter optimization
Simulated binary crossover (SBX) is a real-parameter recombination operator which is commonly used in the evolutionary algorithm (EA) literature. The operator involves a parameter...
Kalyanmoy Deb, Karthik Sindhya, Tatsuya Okabe