Epsilon's Machine Learning Notes
Prelogue
1 Computational and Statistical Learning Theory
- 1.1 PAC Framework
2 Topics in Deep Learning
3 Interpretability
4 Robustness, Adversary and Causality
- 4.1 Applications
  - 4.1.1 Certified Robustness in Text Classification
  - 4.1.2 Adversarial Examples for Natural Language
5 Out-of-Distribution Learning
References
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Epsilon’s Machine Learning Notes

1.1 PAC Framework

The PAC learning framework is the first computational learning model proposed by Valiant in the 1980s.