!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.0 Transitional//EN" "http://www.w3.org/TR/REC-html40/loose.dtd"> CS 591 Section 004 - Randomized Algorithms
Department Seal Sandia Mountains

CS 591-04 "Randomized Algorithms"
Fall 2004


Class Info

The class meets Tuesdays and Thursdays, 4:00-5:15pm in MH 111.

cs591-04 E-mail List:




You are encouraged to work in groups of two or (preferably) three people. Each group should turn in a single write-up. Make sure you put the names of all group members at the top of the hw. Homework grading is likely to be randomized: instead of grading all problems on an assignment, only one or two randomly chosen problems will be graded, and your total score on the assignment will be equal to the score on the chosen problem(s) times the number of problems solved. Please cite whatever sources you use for the hws.



Topics will include some subset of the following:

Text Books

The class will use the following text book:

Tentative Grading Weights

Note: the projects and homeworks can be done in groups but the final must be done without any collaboration.

Grading Methodology

Homework and Final

Your hw and take home final should have the following properties, these will be the criteria used to determine your hw and final grades.


A significant part of this class is the class project. In this project, you will apply mathematical tools learned in this class to solve an algorithmic problem. The project must have a significant analytical component to it where you demonstrate mastery of mathematical tools learned in this class. The project should also contain an empirical component where you do empirical tests which support or complement your analytical results. The main deliverable for the class project is a paper no more than twelve pages in length (not including bibliography and appendix). This paper should be structured as a standard research paper in that it should have an abstract, an introduction, a related work section, a body (containing a section on algorithms a separate section on analysis and a separate section on empirical results), and a conclusion and future work section. Your project grade will depend substantially on this paper.


A necessary prerequisite for this class is a standard undergraduate algorithms course (equivalent to our CS 362). Some basic familiarity with discrete probability is also helpful although not required.

Useful Links


Assignment deadlines are strict: late homework will automatically receive a grade of zero, unless reasonable cause can be shown (which is easy for one, possible for two, and very hard for three or more!); no make-up.
Collaboration is encouraged on all of the homeworks. Usual university policies for withdrawals, incompletes and academic honesty.