CMPUT 675: Approximation Algorithms
Fall 2011, Tue and Thr 2:00-3:20:, in CSC B41.
Instructor: Mohammad R. Salavatipour

Most interesting optimization problems are NP-hard, and therefore it is unlikely that we can find optimal solutions for them efficiently. In many situations, finding a solution that is provably close to an optimal one is also acceptable. The next step is to show this is (almost) the best approximation one can hope for. These are the main goals of this course: find provably good approximation algorithms for the problems that are hard to solve exactly; and prove that finding better approximations are hard. We study some of the common and classical techniques in the design of approximation algorithms, followed by study of some more recent results in this field. Furthermore, we talk about the complexity of approximating these problems. This will be done by learning some classical and some more recent results on hardness of approximation.

CMPUT 304 or strong undergraduate background in theoretical computer science and mathematics. You must also have basic knowledge of graph theory.

There is no required text, but we will be using the following two books:


Lecture notes:

Template for course notes Here is a sample (and in PDF) and its source file.


Grading policy:
This is a theory course (no programming involved). There will be 3 or 4 take home assignments; depending on the number of participants we might have a course project which will be in the form of you presenting one of the more recent (and significant) papers in the area. I will suggest a number of topics for that.
Also, each participant in the course is required to provide scribe notes for one or two weeks of lectures. This is worth 10% of your final mark.
Scribe notes for each week are due the next Monday at noon. Scribe notes must be typed in LaTeX using the template provided above.

Tentative syllabus:

Surely, we won't have time to cover all these topics. Some other topics may be added as we go.

Useful Links:
Here are some useful links to more resources (books, course notes by other people who have taught this course, problems, etc.):

Questions? Send email to me ...