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131
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GECCO
2000
Springer
178views Optimization» more  GECCO 2000»
15 years 8 months ago
Fitness Sharing in Genetic Programming
This paper investigates fitness sharing in genetic programming. Implicit fitness sharing is applied to populations of programs. Three treatments are compared: raw fitness, pure fi...
Robert I. McKay
142
Voted
GECCO
2000
Springer
112views Optimization» more  GECCO 2000»
15 years 8 months ago
Code Compaction Using Genetic Algorithms
One method for compacting executable computer code is to replace commonly repeated sequences of instructions with macro instructions from a decoding dictionary. The size of the de...
Keith E. Mathias, Larry J. Eshelman, J. David Scha...
150
Voted
EMO
2006
Springer
120views Optimization» more  EMO 2006»
15 years 6 months ago
Rule Induction for Classification Using Multi-objective Genetic Programming
Multi-objective metaheuristics have previously been applied to partial classification, where the objective is to produce simple, easy to understand rules that describe subsets of a...
Alan P. Reynolds, Beatriz de la Iglesia
127
Voted
LREC
2010
165views Education» more  LREC 2010»
15 years 6 months ago
Maximum Entropy Classifier Ensembling using Genetic Algorithm for NER in Bengali
In this paper, we propose classifier ensemble selection for Named Entity Recognition (NER) as a single objective optimization problem. Thereafter, we develop a method based on gen...
Asif Ekbal, Sriparna Saha
ICGA
1993
140views Optimization» more  ICGA 1993»
15 years 6 months ago
Expected Allele Coverage and the Role of Mutation in Genetic Algorithms
It is part of the traditional lore of genetic algorithms that low mutation rates lead to efficient search of the solution space, while high mutation rates result in diffusion of s...
David M. Tate, Alice E. Smith