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Coarse-grain parallel genetic algorithms: categorization and new approach
TLDR
This paper describes a number of different coarse-grain GA's, including various migration strategies and connectivity schemes to address the premature convergence problem. Expand
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Dimensionality reduction using genetic algorithms
TLDR
We present an integrated feature extraction and classification approach to feature extraction in which feature selection and extraction and classifier training are performed simultaneously using a genetic algorithm. Expand
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Swarmed feature selection
TLDR
Feature selection is an important part of pattern recognition, helping to overcome the curse of dimensionality problem. Expand
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A Standard GA Approach to Native Protein Conformation Prediction
TLDR
We report here on further work to determine tertiary structures via genetic algorithms. Expand
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Further Research on Feature Selection and Classification Using Genetic Algorithms
TLDR
This paper summarizes work on an approach that combines feature selection and data classiication using Genetic Algorithms. Expand
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The Hierarchical Fair Competition (HFC) Framework for Sustainable Evolutionary Algorithms
TLDR
In this paper, the Hierarchical Fair Competition (HFC) model, including several variants, is proposed as a generic framework for sustainable evolutionary search by transforming the convergent nature of the current EA framework into a non-convergent search process. Expand
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The hierarchical fair competition (HFC) model for parallel evolutionary algorithms
  • J. Hu, E. Goodman
  • Computer Science
  • Proceedings of the Congress on Evolutionary…
  • 12 May 2002
TLDR
The HFC model for evolutionary computation is inspired by the stratified competition often seen in society and biology. Expand
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Feature Extraction Using Genetic Algorithms
This paper summarizes our research on feature selection and extraction from high-dimensionality data sets using genetic algorithms. We have developed a GA-based approach utilizing a feedback linkageExpand
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Predicting conserved water-mediated and polar ligand interactions in proteins using a K-nearest-neighbors genetic algorithm.
Water-mediated ligand interactions are essential to biological processes, from product displacement in thymidylate synthase to DNA recognition by Trp repressor, yet the structural chemistryExpand
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NSGA-Net: neural architecture search using multi-objective genetic algorithm
TLDR
This paper introduces NSGA-Net, a multi-objective genetic algorithm for neural architecture search (NAS). Expand
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