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A Showcase of the Use of Autoencoders in Feature Learning Applications

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From Bioinspired Systems and Biomedical Applications to Machine Learning (IWINAC 2019)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11487))

Abstract

Autoencoders are techniques for data representation learning based on artificial neural networks. Differently to other feature learning methods which may be focused on finding specific transformations of the feature space, they can be adapted to fulfill many purposes, such as data visualization, denoising, anomaly detection and semantic hashing.

This work presents these applications and provides details on how autoencoders can perform them, including code samples making use of an R package with an easy-to-use interface for autoencoder design and training, ruta. Along the way, the explanations on how each learning task has been achieved are provided with the aim to help the reader design their own autoencoders for these or other objectives.

D. Charte is supported by the Spanish Ministry of Science, Innovation and Universities under the FPU National Program (Ref. FPU17/04069). This work is supported by the Spanish National Research Projects TIN2015-68854-R and TIN2017-89517-P.

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Authors and Affiliations

  1. Andalusian Research Institute in Data Science and Computational Intelligence, Department of Computer Science and Artificial Intelligence, Universidad de Granada, Periodista Daniel Saucedo Aranda, s/n, 18071, Granada, Spain

    David Charte & Francisco Herrera

  2. Andalusian Research Institute in Data Science and Computational Intelligence, Computer Science Department, Universidad de Jaén, Campus Las Lagunillas, s/n, 23071, Jaén, Spain

    Francisco Charte & María J. del Jesus

Authors
  1. David Charte
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  2. Francisco Charte
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  3. María J. del Jesus
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  4. Francisco Herrera
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Corresponding author

Correspondence to David Charte .

Editor information

Editors and Affiliations

  1. Universidad Politécnica de Cartagena, Cartagena, Spain

    José Manuel Ferrández Vicente

  2. Universidad Nacional de Educación a Distancia, Madrid, Spain

    José Ramón Álvarez-Sánchez

  3. Universidad Nacional de Educación a Distancia, Madrid, Madrid, Spain

    Félix de la Paz López

  4. Universidad Politécnica de Cartagena, Cartagena, Spain

    Javier Toledo Moreo

  5. The Ohio State University, Columbus, OH, USA

    Hojjat Adeli

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Charte, D., Charte, F., del Jesus, M.J., Herrera, F. (2019). A Showcase of the Use of Autoencoders in Feature Learning Applications. In: Ferrández Vicente, J., Álvarez-Sánchez, J., de la Paz López, F., Toledo Moreo, J., Adeli, H. (eds) From Bioinspired Systems and Biomedical Applications to Machine Learning. IWINAC 2019. Lecture Notes in Computer Science(), vol 11487. Springer, Cham. https://doi.org/10.1007/978-3-030-19651-6_40

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  • DOI: https://doi.org/10.1007/978-3-030-19651-6_40

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-19650-9

  • Online ISBN: 978-3-030-19651-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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