CSC 3030 - Randomized Algorithms

Credits: 4

This course is a self-contained introduction to randomized algorithms and data structures as well as their analysis. The course will focus on understanding the randomized algorithm families (Monte Carlo and Las Vegas), important analysis families (balls and bins, coupon collector, Markov processes, and martingales) as well as analysis techniques (tail bounding, expected run time, etc.). Examples will be drawn from various applications including network algorithms, graph algorithms, machine learning and classification problems, text algorithms, and data structures (e.g., hash tables, skip lists, treaps, etc.).
Prerequisite(s): CSC 2710 with a grade of C or better or instructor permission.
When Offered: Even Springs