Lecture

Nonuniform Learnability and Structural Risk Minimization

Description

This lecture covers the concept of nonuniform learnability and structural risk minimization, discussing the fundamental theorems of PAC learning, the definition of non-uniformly learnable hypothesis classes, and the relationship between PAC learnable classes and SRM. It also explores the conditions under which a hypothesis class is non-uniformly learnable and the implications of this in machine learning.

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