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Learning Theory
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Learning theory
NFL
Lecture 2 : Minimax Rates
Lecture 3 : Statistical Learning
The Existence Of A Priori Distinctions Between Learning Algorithms
On classes of functions for which No Free Lunch results hold
No Free Lunch Theorems
Generalization Bounds
Sharpened Generalization Bounds based on Conditional Mutual Information and an Application to Noisy, Iterative Algorithms
Reasoning About Generalization via Conditional Mutual Information
Generalization
Compositionality decomposed: how do neural networks generalise?