Learning Neural Network Hyperparameters for Machine Translation - 2019

Learning Neural Network Hyperparameters for Machine Translation - 2019

Center for Language & Speech Processing(CLSP), JHU via YouTube Direct link

Pytorch Implementation

15 of 19

15 of 19

Pytorch Implementation

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Learning Neural Network Hyperparameters for Machine Translation - 2019

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  1. 1 Intro
  2. 2 Statistical Machine Translation
  3. 3 Motivation
  4. 4 Grid Search
  5. 5 Method Overview
  6. 6 Common Regularization
  7. 7 Objective Function
  8. 8 Proximal Gradient Methods
  9. 9 Experiments: 5-gram Language Modeling
  10. 10 5-gram Perplexity
  11. 11 Behavior During Training
  12. 12 Key Takeaways
  13. 13 Optimal Hyperparameters Not Universal
  14. 14 Auto-Sizing Transformer Layers
  15. 15 Pytorch Implementation
  16. 16 Beam Search
  17. 17 Perceptron Tuning
  18. 18 Experiment: Tuned Reward
  19. 19 Questions?

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