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Restricted Boltzmann Machines

In: Neural Networks and Deep Learning

Author

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  • Charu Aggarwal

    (International Business Machines, IBM T. J. Watson Research Center)

Abstract

The restricted Boltzmann machine (RBM) is a fundamentally different model from the feed-forward network. Conventional neural networks are input-output mapping networks where a set of inputs is mapped to a set of outputs. On the other hand, RBMs are networks in which the probabilistic states of a network are learned for a set of inputs, which is useful for unsupervised modeling.

Suggested Citation

  • Charu Aggarwal, 2023. "Restricted Boltzmann Machines," Springer Books, in: Neural Networks and Deep Learning, edition 2, chapter 0, pages 231-264, Springer.
    • Handle: RePEc:spr:sprchp:978-3-031-29642-0_7
    DOI: 10.1007/978-3-031-29642-0_7
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