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Conventional Neural Networks
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Classroom Contents
Implicit and Explicit Regularization in Deep Neural Networks
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- 1 Introduction
- 2 Why is deep learning so popular
- 3 Why does deep learning not work
- 4 Supervised learning
- 5 Stochastic gradient descent
- 6 Local optimization
- 7 Prediction error
- 8 What we converge to
- 9 Implicit Regularization
- 10 Stochastic Mirror Descent
- 11 Bregman Divergence
- 12 Stochastic Mirror Descent Algorithm
- 13 Conventional Neural Networks
- 14 SMD
- 15 Summary
- 16 Nonlinear models
- 17 Blessing of dimensionality
- 18 Distribution of weights
- 19 Explicit regularization
- 20 Blessings of dimensionality
