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CEC
2011
IEEE
14 years 2 months ago
Trainer selection strategies for coevolving rank predictors
—Despite the range of applications and successes of evolutionary algorithms, expensive fitness computations often form a critical performance bottleneck. A preferred method of r...
Daniel L. Ly, Hod Lipson
116
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SIGSOFT
2007
ACM
16 years 3 months ago
The impact of input domain reduction on search-based test data generation
There has recently been a great deal of interest in search? based test data generation, with many local and global search algorithms being proposed. However, to date, there has be...
Mark Harman, Youssef Hassoun, Kiran Lakhotia, Phil...
GECCO
2009
Springer
142views Optimization» more  GECCO 2009»
15 years 9 months ago
A stopping criterion based on Kalman estimation techniques with several progress indicators
The need for a stopping criterion in MOEA’s is a repeatedly mentioned matter in the domain of MOOP’s, even though it is usually left aside as secondary, while stopping criteri...
José Luis Guerrero, Jesús Garc&iacut...
146
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ISICA
2007
Springer
15 years 8 months ago
Fast Multi-swarm Optimization with Cauchy Mutation and Crossover Operation
The standard Particle Swarm Optimization (PSO) algorithm is a novel evolutionary algorithm in which each particle studies its own previous best solution and the group’s previous ...
Qing Zhang, Changhe Li, Yong Liu, Lishan Kang
114
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SGAI
2007
Springer
15 years 8 months ago
Evolving a Dynamic Predictive Coding Mechanism for Novelty Detection
Novelty detection is a machine learning technique which identifies new or unknown information in large data sets. We present our current work on the construction of a new novelty...
Simon J. Haggett, Dominique F. Chu, Ian W. Marshal...