Neural Nets for NLP 2017 - Multilingual and Multitask Learning

Neural Nets for NLP 2017 - Multilingual and Multitask Learning

Graham Neubig via YouTube Direct link

Types of Multi-tasking

18 of 19

18 of 19

Types of Multi-tasking

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Neural Nets for NLP 2017 - Multilingual and Multitask Learning

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  1. 1 Intro
  2. 2 Remember, Neural Nets are Feature Extractors!
  3. 3 Types of Learning
  4. 4 Plethora of Tasks in NLP
  5. 5 Rule of Thumb 1: Multitask to Increase Data
  6. 6 Rule of Thumb 2
  7. 7 Standard Multi-task Learning
  8. 8 Examples of Pre-training Encoders
  9. 9 Regularization for Pre-training (e.g. Barone et al. 2017)
  10. 10 Selective Parameter Adaptation
  11. 11 Soft Parameter Tying
  12. 12 Supervised/Unsupervised Adaptation
  13. 13 Supervised Domain Adaptation through Feature Augmentation
  14. 14 Unsupervised Learning through Feature Matching
  15. 15 Multilingual Inputs
  16. 16 Multilingual Structured Prediction/ Multilingual Outputs
  17. 17 Teacher-student Networks for Multilingual Adaptation (Chen et al. 2017)
  18. 18 Types of Multi-tasking
  19. 19 Multiple Annotation Standards

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