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Population-based incremental learning

Known as: PBIL, Population based incremental learning 
In computer science and machine learning, population-based incremental learning (PBIL) is an optimization algorithm, and an estimation of… Expand
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Papers overview

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Highly Cited
2008
Highly Cited
2008
In recent years, interest in studying evolutionary algorithms (EAs) for dynamic optimization problems (DOPs) has grown due to its… Expand
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Highly Cited
2008
Highly Cited
2008
This paper describes a novel feature selection algorithm for unsupervised clustering, that combines the clustering ensembles… Expand
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Highly Cited
2008
Highly Cited
2008
In this paper we propose a new probability update rule and sampling procedure for population-based incremental learning. These… Expand
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Highly Cited
2008
Highly Cited
2008
This book constitutes the joint refereed proceedings of six workshops on evolutionary computing, EvoWorkshops 2004, held together… Expand
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Highly Cited
2007
Highly Cited
2007
The work in this paper presents the use of population-based incremental learning (PBIL), one of the classic single-objective… Expand
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Highly Cited
2005
Highly Cited
2005
Evolutionary algorithms have been widely used for stationary optimization problems. However, the environments of real world… Expand
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Highly Cited
2005
Highly Cited
2005
Probabilistic Incremental Learning PBIL has been proposed as a model for binary coded evolutionary algorithms where the… Expand
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Highly Cited
1998
Highly Cited
1998
An alternative to Darwinian-like artificial evolution is offered by Population-Based Incremental Learning (PBIL): this algorithm… Expand
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1998
1998
  • C. Fyfe
  • Soft Comput.
  • 1998
  • Corpus ID: 12058954
Abstract We investigate a recently developed abstraction of genetic algorithms (GAs) in which a population of GAs in any… Expand
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Highly Cited
1994
Highly Cited
1994
Genetic algorithms (GAs) are biologically motivated adaptive systems which have been used, with varying degrees of success, for… Expand
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