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  • Ravichandran, Naresh Balaji, et al. (author)
  • Brain-Like Approaches to Unsupervised Learning of Hidden Representations - A Comparative Study
  • 2021
  • In: Artificial Neural Networks And Machine Learning,  ICANN 2021, Pt V. - Cham : Springer Nature. ; , s. 162-173
  • Conference paper (peer-reviewed)abstract
    • Unsupervised learning of hidden representations has been one of the most vibrant research directions in machine learning in recent years. In this work we study the brain-like Bayesian Confidence Propagating Neural Network (BCPNN) model, recently extended to extract sparse distributed high-dimensional representations. The usefulness and class-dependent separability of the hidden representations when trained on MNIST and Fashion-MNIST datasets is studied using an external linear classifier and compared with other unsupervised learning methods that include restricted Boltzmann machines and autoencoders.
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Type of publication
conference paper (1)
Type of content
peer-reviewed (1)
Author/Editor
Lansner, Anders, Pro ... (1)
Herman, Pawel, 1979- (1)
Ravichandran, Naresh ... (1)
University
Royal Institute of Technology (1)
Language
English (1)
Research subject (UKÄ/SCB)
Natural sciences (1)
Year
2021 (1)

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