Welcome to the home page for the Computer Science Department's Graduate Algorithms course CLA CS 530. This is the starting point for online course information and documentation.
CS 530 is the central graduate algorithms course in the computer science curriculum. It serves as the a core graduate theory course. It is the successor to the undergraduate algorithms course, CS 330, and has this course as a prerequisite. In CS 530 students will learn fundamental algorithm design and algorithm analysis at the graduate level. The following list of pointers provides access to information concerning the course, the students and the instructors.
Most recent CS 530 Course News.
Most recent class assignment: HW 5
Some extra material and notes from class: Example of the Ford Fulkerson algorithm
The powerpoint of some nice lectures on linear programming from a course Taught by Robert Sedgewick and Kevin Wayne at Princeton.
Notes by Lenore Cowen (Tufts University, with scribe Stephanie Tauber) with good examples of approximation algorithms for the metric TSP problem.
A few pages on randomized algorithms covering what was discussed in class. (See page 5 for Freivalds algorithm.)