CS 795 Syllabus (Fall 2008)

CS 795 Fall 2008
Approximation Algorithms

Lecture Time: Thursday 4:30 pm - 7:10 pm
Location: Innovation Hall 134
Course webpage: http://www.cs.gmu.edu/~lifei/teaching/cs795_fall08/
Credit: 3

Instructor: Fei Li, Office 443 ST II, email:
Office hours: Friday 4:00pm - 6:00pm


Course Overview:

The area of approximation algorithms is aimed at giving provable guarantees on the performance of algorithms for hard problems. In this course, we will learn approximation algorithms and their analysis.


CS 483. Please contact with the instructor if you are not sure.

Recommended Books:

Approximation Algorithms, by Vijay V. Vazirani, Springer, 2003

Introduction to Algorithms, by Thomas H. Corman, Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein, The McGraw-Hill Companies, 2nd Edition 2001

Randomized Algorithms, by Rajeev Motwani and Prabhakar Raghavan, Cambridge University Press, 1995

Course Materials: (Tentative)

Lecture Date Topic Lecture Notes Scope Note
1 August 28 NP-hardness and reduction      
2 September 4 Limits of tractability, Set cover, Vertex cover      
3 September 11 Steiner tree, TSP, Euclidean TSP      
4 September 18 Knapsack, Scheduling, Bin packing      
5 September 25 MAX SAT, LP relaxation, Randomized solutions      
6 October 2 Cut problems      
7 October 9 Primal-dual method      
8 October 16 Primal-dual method      
9 October 23 Facility location, center problems      
10 November 6 Semi-definite programming      
11 November 13 Survivable network design, Couting problems, Markov chains      
12 November 20 Local ratio      
  November 27       No class. Thanksgiving.
13 December 4       Project presentations

Paper List (Papers are to be added in this list along the course):


Tentative Grading:

    1. Assignments (20%)

    2. A survey about existing literatures on a NP-hard problem or a technique (20%)

    3. Two presentations (20%)

    4. A project. You can work on designing and analyzing an approximation algoirthms for a NP-hard problem or you can implement some known approximation algorithms for some specific applications, and provide experimental analysis. (40%)

Academic Honesty:

The integrity of the University community is affected by the individual choices made by each of us. GMU has an Honor Code with clear guidelines regarding academic integrity. Three fundamental and rather simple principles to follow at all times are that: (1) all work submitted be your own; (2) when using the work or ideas of others, including fellow students, give full credit through accurate citations; and (3) if you are uncertain about the ground rules on a particular assignment, ask for clarification. No grade is important enough to justify academic misconduct. Plagiarism means using the exact words, opinions, or factual information from another person without giving the person credit. Writers give credit through accepted documentation styles, such as parenthetical citation, footnotes, or endnotes. Paraphrased material must also be cited, using MLA or APA format. A simple listing of books or articles is not sufficient. Plagiarism is the equivalent of intellectual robbery and cannot be tolerated in the academic setting. If you have any doubts about what constitutes plagiarism, please see me.

Disability Statement:

If you have a learning or physical difference that may affect your academic work, you will need to furnish appropriate documentation to the Disability Resource Center. If you qualify for accommodation, the DRC staff will give you a form detailing appropriate accommodations for your instructor. In addition to providing your professors with the appropriate form, please take the initiative to discuss accommodation with them at the beginning of the semester and as needed during the term. Because of the range of learning differences, faculty members need to learn from you the most effective ways to assist you. If you have contacted the Disability Resource Center and are waiting to hear from a counselor, please tell me.