Lecture

PAC Learning: Empirical Risk Minimization

In course

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Description

This lecture delves into quantifying how much an algorithm learns using the PAC learning framework, introducing the Empirical Risk Minimization principle, discussing the ill-posed nature of learning, the need for inductive bias, and different predictor/hypothesis spaces.

Official source

https://mediaspace.epfl.ch/media/0_4mk68fmp

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