Gradients Are Not All You Need - Machine Learning Research Paper Explained

Gradients Are Not All You Need - Machine Learning Research Paper Explained

Yannic Kilcher via YouTube Direct link

- Foreword

1 of 12

1 of 12

- Foreword

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Gradients Are Not All You Need - Machine Learning Research Paper Explained

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  1. 1 - Foreword
  2. 2 - Intro & Overview
  3. 3 - Backpropagation through iterated systems
  4. 4 - Connection to the spectrum of the Jacobian
  5. 5 - The Reparameterization Trick
  6. 6 - Problems of reparameterization
  7. 7 - Example 1: Policy Learning in Simulation
  8. 8 - Example 2: Meta-Learning Optimizers
  9. 9 - Example 3: Disk packing
  10. 10 - Analysis of Jacobians
  11. 11 - What can be done?
  12. 12 - Just use Black-Box methods

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