Welcome to the home page for the Computer Science Department's Graduate Randomized Algorithms and Computation class, CS 537. This is the starting point for online course information and documentation.
Here is the most recent CS 537 Course News.
Here is the most recent homework - part 1, and homework - part 2, due on Thursday, December 12.
Past homeworks: Homework 1, homework 2, homework 3, homework 4
Some notes from our (recommended) textbook including sections of Chapter 7 concerning algebraic techniques (Freivalds, polynomial identity testing and matching), and some relevant parts of the appendices on math background and intro probability.
Here is the midterm together with brief answers following each question.
Here is a List of Student Talks with Outlines and Lecture Notes which have been given this semester.
A short list of practice problems on basic discrete probability can be found here.
CS 537 is an advanced graduate algorithms and theory course in the computer science curriculum. It serves as a core graduate theory course and satisfies the breadth requirement. It is the successor to the graduate algorithms course, CS 530, and has this course or CS 330 as a prerequisite. It also requires considerable background in discrete probability and fundamental mathematical skills. In CS 537 students will learn randomized algorithm design and analysis at the graduate level. The following list of pointers provides access to information concerning the course, the students and the instructors.
Page prepared by Steve Homer