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Classroom Contents
Overview of Quantum Learning Theory - Lecture 1
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- 1 Intro
- 2 Quantum machine learning
- 3 Quantum learning theory
- 4 A Theory of the Learnable
- 5 Classical learner using classical examples
- 6 Learning model: classical PAC learning
- 7 Quantum PAC learning
- 8 Vapnik and Chervonenkis (VC) dimension
- 9 VC dimension characterizes PAC sample complexity
- 10 Quantum sample complexity = Classical sample complexity
- 11 Proof approach: Pretty Good Measurement
- 12 Sample complexity lower bound via PGM
- 13 Random classification noise
- 14 Agnostic learning
