Lecture 23: Probability Amplification
November 19th, 2007We covered the section on global min cuts in the textbook. In addition, I talked about Chernoff bounds as a method for amplifying the probability of success of an algorithm. Here are some notes on this topic.
I also talked about the power of two choices: the idea that when placing balls in bins, merely choosing two locations at random and picking the better one can lead to an exponential improvement in the maximum load of a bin (from $latex \log{n}$ to $latex \log\log{n}$). A nice survey that reviews this idea (and gives three different proofs of the main theorem) can be found here.