Departments' graduate courses

Course start and periodicity may vary. Please see details for each course for up-to-date information. The courses are managed and administered by the respective departments. For more information about the courses, how to sign up, and other practical issues, please contact the examiner or course contact to be found in the course information.

Approximation and Randomized Algorithms

  • Course code: FDAT060
  • Course higher education credits: 7.5
  • Graduate school: Computer Science and Engineering
  • Course is normally given: LP 2
  • Language: The course will be given in English

Course topic (brief)
This seminar course introduces the students to the areas of approximation and randomized algorithm. We will review some classical results in these areas. Pre-requisite: A graduate-level course on Algorithms, and mathematical maturity.

Organization of the course
The course is a seminar course. The students are expected to attend the seminars, participate in the discussion, and present papers/book chapters assigned by the teachers.

Attendance and participation in lectures, presentation of a lecture, and a final oral exam. Please contact the responsible teachers about details on the precise schedule and starting date.  

Probability and Computing: Randomized Algorithsm and Probabilistic Analysis : Eli Upfal and Michael Mitzenmacher Approximation Algorithms: Vijay Vazirani..
Chien-Chung Huang e-mail: phone: +46 31 772 16 99
More information

Page manager Published: Tue 22 Aug 2017.