A Survey: Time Travel in Deep Learning Space: An Introduction to Deep Learning Models and How Deep Learning Models Evolved from the Initial Ideas

Preprint English OPEN
Wang, Haohan; Raj, Bhiksha;
(2015)
  • Subject: Computer Science - Neural and Evolutionary Computing | Computer Science - Learning
    arxiv: Quantitative Biology::Neurons and Cognition | Computer Science::Neural and Evolutionary Computation

This report will show the history of deep learning evolves. It will trace back as far as the initial belief of connectionism modelling of brain, and come back to look at its early stage realization: neural networks. With the background of neural network, we will gradual... View more
  • References (4)

    [37] OJA, E., AND KARHUNEN, J. On stochastic approximation of the eigenvectors and eigenvalues of the expectation of a random matrix. Journal of mathematical analysis and applications 106, 1 (1985), 69-84.

    [38] ORPONEN, P. Computational complexity of neural networks: a survey. Nordic Journal of Computing 1, 1 (1994), 94-110.

    [39] PASCANU, R., GULCEHRE, C., CHO, K., AND BENGIO, Y. How to construct deep recurrent neural networks. arXiv preprint arXiv:1312.6026 (2013).

    [40] PERSON, K. On lines and planes of closest fit to system of points in space. philiosophical magazine, 2, 559-572, 1901.

  • Metrics
Share - Bookmark