CS2013-final-report

and other applications including Baseball Elimination. Randomized
algorithms including randomized median, randomized min-cut, randomized
quicksort, and Rabin-Karp string matching. We cover the geometric problem
of finding the closest pair of points in the plane and develop the standard
randomized solution based on hashing. Sometimes we cover linear
programming. Very little number theoretic and geometric algorithms are
covered due to time. We spend two lectures on approximation algorithms
because it is my research area.
DS
Discrete
Probability
We review concepts from discrete probability in support of randomized
algorithms. This includes expectation, variance, and (very quickly)
concentration bounds (we use these to prove that many of our algorithms run
in their expected time with very high probability)
2
Other comments
There is some overlap with the topics covered here and DS/Graphs and Trees.
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