Genetic Programming with Local Improvement for Visual Learning from Examples
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- @InProceedings{Krawiec-chapter:2001,
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author = "Krzysztof Krawiec",
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year = "2001",
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title = "Genetic Programming with Local Improvement for Visual
Learning from Examples",
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booktitle = "Proceedings 9th International Conference on Computer
Analysis of Images and Patterns, CAIP 2001",
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editor = "W. Skarbek",
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volume = "2124",
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series = "Lecture Notes in Computer Science",
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pages = "209--216",
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address = "Warsaw, Poland",
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publisher_address = "Heidelberg",
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month = sep # " 5-7",
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publisher = "Springer-Verlag",
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keywords = "genetic algorithms, genetic programming, visual
learning, genetic local search, learning from
examples",
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ISSN = "0302-9743",
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DOI = "doi:10.1007/3-540-44692-3_26",
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abstract = "This paper investigates the use of evolutionary
programming for the search of hypothesis space in
visual learning tasks. The general goal of the project
is to elaborate human-competitive procedures for
pattern discrimination by means of learning based on
the training data (set of images). In particular, the
topic addressed here is the comparison between the
'standard' genetic programming (as defined by Koza
[13]) and the genetic programming extended by local
optimization of solutions, so-called genetic local
search. The hypothesis formulated in the paper is that
genetic local search provides better solutions (i.e.
classifiers with higher predictive accuracy) than the
genetic search without that extension. This supposition
was positively verified in an extensive comparative
experiment of visual learning concerning the
recognition of handwritten characters.",
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notes = "A1 Institute of Computing Science, Poznan University
of Technology, Piotrowo 3A, 60965 Poznan, Poland
krawiec@cs.put.poznan.pl",
- }
Genetic Programming entries for
Krzysztof Krawiec
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