Theory of Meta-Learning
Theoretical understanding.
Learning to Learn
Fast adaptation. Meta-parameters.
Convergence
Convergence guarantees. Gradient-based meta-learning.
Bounds
Sample complexity. Generalization bounds.
Key Takeaways
- Fast adaptation theory
- Gradient-based meta-learning
- Generalization bounds