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

The previous assignments were: HW 1, HW 2, HW 3, HW 4

Some answers to homework assignments and the midterm: HW 1, HW 2, HW 3, HW 4

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.)

- An overview of course policy.
- Course Information
- Computer Science Department Information
- Help and Other Places in Cyberspace (courtesy of A. Kfoury)
- A Historical Note
- Steve Seiden's Cheat Sheet(ten pages of commonly used formulas in computer science).