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» On the Brittleness of Evolutionary Algorithms
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RECSYS
2010
ACM
15 years 6 months ago
Incremental collaborative filtering via evolutionary co-clustering
Collaborative filtering is a popular approach for building recommender systems. Current collaborative filtering algorithms are accurate but also computationally expensive, and so ...
Mohammad Khoshneshin, W. Nick Street
AMC
2007
115views more  AMC 2007»
15 years 6 months ago
Evolutionary programming based on non-uniform mutation
Abstract–A new evolutionary programming algorithm (NEP) using the non-uniform mutation operator instead of Gaussian or Cauchy mutation operators is proposed. NEP has the merits o...
Xinchao Zhao, Xiao-Shan Gao, Ze-Chun Hu
GECCO
2004
Springer
112views Optimization» more  GECCO 2004»
15 years 11 months ago
Some Issues on the Implementation of Local Search in Evolutionary Multiobjective Optimization
This paper discusses the implementation of local search in evolutionary multiobjective optimization (EMO) algorithms for the design of a simple but powerful memetic EMO algorithm. ...
Hisao Ishibuchi, Kaname Narukawa
ATAL
2006
Springer
15 years 10 months ago
Evolutionary Optimization of ZIP60: A Controlled Explosion in Hyperspace
The "ZIP" adaptive trading algorithm has been demonstrated to outperform human traders in experimental studies of continuous double auction (CDA) markets. The original Z...
Dave Cliff
GECCO
2005
Springer
129views Optimization» more  GECCO 2005»
15 years 12 months ago
Evolutionary change in developmental timing
This paper presents a mutation-based evolutionary algorithm that evolves genotypic genes for regulating developmental timing of phenotypic values. The genotype sequentially genera...
Kei Ohnishi, Kaori Yoshida