3. Correlation-Based Neural Learning and Machine Learning

  1. Zhe Chen1,
  2. Simon Haykin2,
  3. Jos J. Eggermont3 and
  4. Suzanna Becker2

Published Online: 1 MAR 2007

DOI: 10.1002/9780470171455.ch3

Correlative Learning: A Basis for Brain and Adaptive Systems

Correlative Learning: A Basis for Brain and Adaptive Systems

How to Cite

Chen, Z., Haykin, S., Eggermont, J. J. and Becker, S. (2007) Correlation-Based Neural Learning and Machine Learning, in Correlative Learning: A Basis for Brain and Adaptive Systems, John Wiley & Sons, Inc., Hoboken, NJ, USA. doi: 10.1002/9780470171455.ch3

Author Information

  1. 1

    RIKEN Brain Science Institute, Japan

  2. 2

    McMaster University, Canada

  3. 3

    University of Calgary, Canada

Publication History

  1. Published Online: 1 MAR 2007
  2. Published Print: 27 SEP 2007

ISBN Information

Print ISBN: 9780470044889

Online ISBN: 9780470171455

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Keywords:

  • computational neural models and learning algorithms;
  • correlation-based synaptic plasticity and learning rules;
  • independent component analysis (ICA), and slow feature analysis (SFA)

Summary

This chapter contains sections titled:

  • Correlation as a Mathematical Basis for Learning

  • Information-Theoretic Learning

  • Correlation-Based Computational Neural Models

  • Appendix 3A: Mathematical Analysis of Hebbian Learning

  • Appendix 3B: Necessity and Convergence of Anti-Hebbian Learning

  • Appendix 3C: Link between Hebbian Rule and Gradient Descent

  • Appendix 3D: Reconstruction Error in Linear and Quadratic PCA

  • Bibliographical Notes

  • Notes