Semantic Learning Machine: A Feedforward Neural Network Construction Algorithm Inspired by Geometric Semantic Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8051
- @InProceedings{conf/epia/GoncalvesSF15,
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author = "Ivo Goncalves and Sara Silva and Carlos M. Fonseca",
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title = "Semantic Learning Machine: {A} Feedforward Neural
Network Construction Algorithm Inspired by Geometric
Semantic Genetic Programming",
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booktitle = "Progress in Artificial Intelligence - 17th Portuguese
Conference on Artificial Intelligence, {EPIA} 2015",
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year = "2015",
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editor = "Francisco C. Pereira and Penousal Machado and
Ernesto Costa and Amilcar Cardoso",
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volume = "9273",
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series = "Lecture Notes in Computer Science",
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pages = "280--285",
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address = "Coimbra, Portugal",
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month = sep # " 8-11",
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publisher = "Springer",
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keywords = "genetic algorithms, genetic programming",
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isbn13 = "978-3-319-23484-7",
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bibdate = "2015-08-26",
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bibsource = "DBLP,
http://dblp.uni-trier.de/db/conf/epia/epia2015.html#GoncalvesSF15",
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URL = "http://dx.doi.org/10.1007/978-3-319-23485-4",
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DOI = "doi:10.1007/978-3-319-23485-4_28",
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size = "6 pages",
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abstract = "Geometric Semantic Genetic Programming (GSGP) is a
recently proposed form of Genetic Programming in which
the fitness landscape seen by its variation operators
is unimodal with a linear slope by construction and,
consequently, easy to search. This is valid across all
supervised learning problems. In this paper we propose
a feedforward Neural Network construction algorithm
derived from GSGP. This algorithm shares the same
fitness landscape as GSGP, which allows an efficient
search to be performed on the space of feedforward
Neural Networks, without the need to use
backpropagation. Experiments are conducted on real-life
multidimensional symbolic regression datasets and
results show that the proposed algorithm is able to
surpass GSGP, with statistical significance, in terms
of learning the training data. In terms of
generalization, results are similar to GSGP.",
- }
Genetic Programming entries for
Ivo Goncalves
Sara Silva
Carlos M Fonseca
Citations