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» An evolutionary method for complex-process optimization
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100
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GECCO
2005
Springer
152views Optimization» more  GECCO 2005»
15 years 8 months ago
GAMM: genetic algorithms with meta-models for vision
Recent adaptive image interpretation systems can reach optimal performance for a given domain via machine learning, without human intervention. The policies are learned over an ex...
Greg Lee, Vadim Bulitko
118
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GECCO
2005
Springer
144views Optimization» more  GECCO 2005»
15 years 8 months ago
Multiobjective hBOA, clustering, and scalability
This paper describes a scalable algorithm for solving multiobjective decomposable problems by combining the hierarchical Bayesian optimization algorithm (hBOA) with the nondominat...
Martin Pelikan, Kumara Sastry, David E. Goldberg
GECCO
2004
Springer
15 years 7 months ago
Metaheuristics for Natural Language Tagging
Abstract. This work compares different metaheuristics techniques applied to an important problem in natural language: tagging. Tagging amounts to assigning to each word in a text ...
Lourdes Araujo, Gabriel Luque, Enrique Alba
KES
2004
Springer
15 years 7 months ago
Extracting Stellar Population Parameters of Galaxies from Photometric Data Using Evolution Strategies and Locally Weighted Linea
There is now a huge amount of high quality photometric data available in the literature whose analysis is bound to play a fundamental role in studies of the formation and evolution...
Luis Alvarez, Olac Fuentes, Roberto Terlevich
GECCO
2010
Springer
129views Optimization» more  GECCO 2010»
15 years 7 months ago
A probabilistic functional crossover operator for genetic programming
The original mechanism by which evolutionary algorithms were to solve problems was to allow for the gradual discovery of sub-solutions to sub-problems, and the automated combinati...
Josh C. Bongard