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The Foundation and Advances of Deep Learning

  • Liang LinEmail author
  • Dongyu Zhang
  • Ping Luo
  • Wangmeng Zuo
Chapter

Abstract

The past decade has witnessed the rapid development of feature representation learning, especially deep learning. Deep learning methods have achieved great success in many applications, including computer vision, and natural language processing. In this chapter, we present a short review of the foundation of deep learning, i.e., artificial neural network, and introduce some new techniques in deep learning.

References

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    W. Guangrun, P. Jiefeng, L. Ping, W. Xinjiang, L. Liang, Batch kalman normalization: towards training deep neural networks with micro-batches, arXiv preprint arXiv:1802.03133 (2018)
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    S. Ioffe, C. Szegedy, Batch normalization: accelerating deep network training by reducing internal covariate shift, arXiv preprint arXiv:1502.03167 (2015)
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    R.E. Kalman et al., A new approach to linear filtering and prediction problems. J. Basic Eng. 82(1), 35–45 (1960)MathSciNetCrossRefGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Liang Lin
    • 1
    Email author
  • Dongyu Zhang
    • 1
  • Ping Luo
    • 2
  • Wangmeng Zuo
    • 3
  1. 1.School of Data and Computer ScienceSun Yat-sen UniversityGuangzhouChina
  2. 2.School of Information EngineeringThe Chinese University of Hong KongHong KongHong Kong
  3. 3.School of Computer ScienceHarbin Institute of TechnologyHarbinChina

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