Active learning with adaptive grids
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Date
2001
Publication Type
Conference Paper
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yes
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Abstract
Given some optimization problem and a series of typically expensive trials of solution candidates taken from a search space, how can we efficiently select the next candidate? We address this fundamental problem using adaptive grids inspired by Kohonen’s self-organizing map. Initially the grid divides the search space into equal simplexes. To select a candidate we uniform randomly first select a simplex, then a point within the simplex. Grid nodes are attracted by candidates that lead to improved evaluations. This quickly biases the active data selection process towards promising regions, without loss of ability to deal with”surprising” global optima in other areas. On standard benchmark functions the technique performs more reliably than the widely used covariance matrix adaptation evolution strategy.
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published
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Book title
Artificial neural networks-ICANN 2001 : International Conference, Vienna, Austria, August 21-25, 2001 : proceedings
Journal / series
Volume
2130
Pages / Article No.
436 - 442
Publisher
Springer
Event
International Conference on Artificial Neural Networks (ICANN 2001)
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Methods
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03499 - Koumoutsakos, Petros (ehemalig) / Koumoutsakos, Petros (former)