Chapter 1: Introduction, Discrete Probability
Spaces, Min-CutChapter 1: Introduction, Discrete Probability
Spaces, Min-Cut
Chapter 2: Random Variables, Expectation,
Discrete Probability Distributions, Variance, Standard Deviation,
Chebyshev Inequality, Coupon Collector
Chapter 4ALarge Deviation Bounds Chapter 4B: Packet Routing on the n-cube
Chapter 6: The Probabilistic Method (and Hashing)
Chapter 12: Martingales
Chapters 10-11: The Monte Carlo Method
Chapter 14A: Statistical Learning - Learning from Examples
Chapter 14B: VC dimension and Uniform Convergence
Last Updated: Mar 31 2014