Topic and Slides
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Notes
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Additional Readings
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Introduction, Sample complexity bound for
learning axis parallel rectangles.
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Chapter 1 of Kearnes Vazirani book (COLT book)
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Probability Concepts
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Appendix B of UML book
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Definition of PAC Learning
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Chapter 1-2 of Shai Shalev-Shwartz and Shai Ben-David book (UML book)
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A Theory of the Learnable - Valiant
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PAC Learnability of Finite Hypothesis Classes, Empirical Risk Minimization
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Chapter 3 of UML book
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Agnostic PAC Learnability of Finite Hypothesis Class, Uniform Convergence
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Chapter 4 of UML book
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VC dimension
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Chapter 6 of UML book
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Shattering
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Chapter 6 of UML book
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Growth Function
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Chapter 6 of UML book
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Fundamental Theorem of Statistical Learning Theory
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Chapter 6 of UML book
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Rademacher Complexity
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Chapter 26 of UML book
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Nonuniform Learnability, Structural Risk Minimization
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Chapter 7 of UML book
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Weak Learnability, Adaboost
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Chapter 10 of UML book
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Adaboost by Prof. Robert Schapire
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Online Learning
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Chapter 21 of UML book
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Talk by Prof. Avrim Blum
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Perceptron Learning
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Chapter 21,of UML book
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Convex learning Problems
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Chapter 12 of UML book
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