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Resource-Aware Data Stream Mining Using the Restricted Boltzmann Machine

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Artificial Intelligence and Soft Computing (ICAISC 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11509))

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Abstract

In this paper, we consider the problem of data stream mining with an application of the Restricted Boltzmann Machine (RBM). If the data incoming rate is very fast, an appropriate algorithm should be resource-aware and work as fast as possible. Two RBM learning algorithms are investigated, i.e. the Contrastive Divergence and the Persistent Contrastive Divergence. We test three strategies for dealing with a buffer overflow in the case of high-speed data streams: load shedding, minibatch resizing, and controlling the number of Gibbs steps in the learning algorithm. Considered approaches are verified on the real MNIST dataset which is treated as a part of a data stream.

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Acknowledgments

This work was supported by the Polish National Science Centre under grant no. 2017/27/B/ST6/02852.

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Authors and Affiliations

  1. Institute of Computational Intelligence, Czestochowa University of Technology, Czestochowa, Poland

    Maciej Jaworski, Leszek Rutkowski & Piotr Duda

  2. Information Technology Institute, University of Social Sciences, Łódź, Poland

    Leszek Rutkowski & Andrzej Cader

  3. Clark University, Worcester, MA, USA

    Andrzej Cader

Authors
  1. Maciej Jaworski
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  2. Leszek Rutkowski
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  3. Piotr Duda
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  4. Andrzej Cader
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Corresponding author

Correspondence to Maciej Jaworski .

Editor information

Editors and Affiliations

  1. Częstochowa University of Technology, Częstochowa, Poland

    Leszek Rutkowski

  2. Częstochowa University of Technology, Częstochowa, Poland

    Rafał Scherer

  3. Częstochowa University of Technology, Częstochowa, Poland

    Marcin Korytkowski

  4. University of Alberta, Edmonton, AB, Canada

    Witold Pedrycz

  5. AGH University of Science and Technology, Kraków, Poland

    Ryszard Tadeusiewicz

  6. University of Louisville, Louisville, KY, USA

    Jacek M. Zurada

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Jaworski, M., Rutkowski, L., Duda, P., Cader, A. (2019). Resource-Aware Data Stream Mining Using the Restricted Boltzmann Machine. In: Rutkowski, L., Scherer, R., Korytkowski, M., Pedrycz, W., Tadeusiewicz, R., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2019. Lecture Notes in Computer Science(), vol 11509. Springer, Cham. https://doi.org/10.1007/978-3-030-20915-5_35

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