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on
1
Intro
2
Expected Value
3
Theorem
4
Proof
5
Ghost Sample
6
Bounds
7
Randomness
8
Summary
9
Finite Hypothesis Space
10
Conclusion
11
PAC Learning
Description:
Explore advanced concepts in statistical learning with Robert Schapire from Microsoft Research in this hour-long lecture. Delve into topics such as expected value theorems, ghost sample bounds, and PAC learning. Gain insights into finite hypothesis spaces and the role of randomness in statistical learning. Enhance your understanding of statistical learning theory through detailed proofs and comprehensive explanations provided by an expert in the field.

Statistical Learning IV - Robert Schapire, Microsoft Research

Paul G. Allen School
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