Explorations of the Semantic Learning Machine Neuroevolution Algorithm: Dynamic Training Data Use, Ensemble Construction Methods, and Deep Learning Perspectives
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- @InProceedings{Goncalves:2019:GPTP,
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author = "Ivo Goncalves and Marta Seca and Mauro Castelli",
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title = "Explorations of the Semantic Learning Machine
Neuroevolution Algorithm: Dynamic Training Data Use,
Ensemble Construction Methods, and Deep Learning
Perspectives",
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booktitle = "Genetic Programming Theory and Practice XVII",
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year = "2019",
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editor = "Wolfgang Banzhaf and Erik Goodman and
Leigh Sheneman and Leonardo Trujillo and Bill Worzel",
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pages = "39--62",
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address = "East Lansing, MI, USA",
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month = "16-19 " # may,
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publisher = "Springer",
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keywords = "genetic algorithms, genetic programming, Semantic
learning machine, Neuroevolution, Evolutionary machine
learning, Artificial neural networks, ANN, Deep
learning Deep semantic learning machine",
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isbn13 = "978-3-030-39957-3",
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DOI = "doi:10.1007/978-3-030-39958-0_3",
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abstract = "The recently proposed Semantic Learning Machine (SLM)
neuroevolution algorithm is able to construct Neural
Networks (NNs) over unimodal error landscapes in any
supervised learning problem where the error is measured
as a distance to the known targets. This chapter
studies how different methods of dynamically using the
training data affect the resulting generalization of
the SLM algorithm. Across four real-world binary
classification datasets, SLM is shown to outperform the
Multi-layer Perceptron, with statistical significance,
after parameter tuning is performed in both algorithms.
Furthermore, this chapter also studies how different
ensemble constructions methods influence the resulting
generalization. The results show that the stochastic
nature of SLM already confers enough diversity to the
ensembles such that Bagging and Boosting cannot improve
upon a simple averaging ensemble construction method.
Finally, some initial results with SLM and
Convolutional NNs are presented and future Deep
Learning perspectives are discussed.",
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notes = "Part of \cite{Banzhaf:2019:GPTP}, published after the
workshop",
- }
Genetic Programming entries for
Ivo Goncalves
Marta Seca
Mauro Castelli
Citations