A New First-Order Meta-Learning Algorithm with Convergence Guarantees

The episode discusses 'A New First-Order Meta-Learning Algorithm with Convergence Guarantees,' a paper from EPFL. Hosts analyze how this method achieves memory efficiency and convergence guarantees by reformulating the meta-gradient using finite differences, making meta-learning viable for large models.

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