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FSMNLP
2005
Springer
15 years 7 months ago
Algorithms for Minimum Risk Chunking
Abstract. Stochastic finite automata are useful for identifying substrings (chunks) within larger units of text. Relevant applications include tokenization, base-NP chunking, name...
Martin Jansche
GECCO
2005
Springer
132views Optimization» more  GECCO 2005»
15 years 7 months ago
A statistical learning theory approach of bloat
Code bloat, the excessive increase of code size, is an important issue in Genetic Programming (GP). This paper proposes a theoretical analysis of code bloat in the framework of sy...
Sylvain Gelly, Olivier Teytaud, Nicolas Bredeche, ...
GECCO
2005
Springer
197views Optimization» more  GECCO 2005»
15 years 7 months ago
Performance assessment of an artificial immune system multiobjective optimizer by two improved metrics
In this study, we introduce two improved assessment metrics of multiobjective optimizers, Nondominated Ratio and Spacing Distribution, and analyze their rationality and validity. ...
Maoguo Gong, Licheng Jiao, Haifeng Du, Ronghua Sha...
GECCO
2005
Springer
116views Optimization» more  GECCO 2005»
15 years 7 months ago
Measuring, enabling and comparing modularity, regularity and hierarchy in evolutionary design
For computer-automated design systems to scale to complex designs they must be able to produce designs that exhibit the characteristics of modularity, regularity and hierarchy –...
Gregory Hornby
GECCO
2005
Springer
150views Optimization» more  GECCO 2005»
15 years 7 months ago
Population-based incremental learning with memory scheme for changing environments
In recent years there has been a growing interest in studying evolutionary algorithms for dynamic optimization problems due to its importance in real world applications. Several a...
Shengxiang Yang