Fall 2020 - CMPT 409 D200
Special Topics in Theoretical Computing Science (3)
Class Number: 6642
Delivery Method: In Person
Current topics in theoretical computing science depending on faculty and student interest.
Most interesting optimization problems are NP-hard. For an NP-hard problem, it is impossible to have an algorithm which gives an optimal solution efficiently (in polynomial time) for any input instance of the problem unless P=NP. Approximation are powerful and widely used approaches for tackling hard optimization problems. An approximation algorithm finds a near-optimal solution with guaranteed accuracy efficiently for any input instance. Randomized algorithms are another powerful and widely used approach to tackle problems for which efficient deterministic algorithms are not known. The course will cover the fundamentals on the design and analysis of approximation and randomized algorithms for discrete optimization problems. By completing this course, students are expected to be able to design approximation and randomized algorithms for their own problems, prove and analyze the correctness and efficiency of their algorithms, and apply theoretical analysis to the study of heuristics.
- Basic probability: linearity of expectation, concentration inequalities
- Approximation algorithms for discrete optimization problems
- Randomized algorithms
- Linear programming
- Semidefinite programming
- Sublinear time algorithms
- PCP theorem and hardness of approximation
To be discussed in class.
ACADEMIC INTEGRITY: YOUR WORK, YOUR SUCCESS
SFU’s Academic Integrity web site http://www.sfu.ca/students/academicintegrity.html is filled with information on what is meant by academic dishonesty, where you can find resources to help with your studies and the consequences of cheating. Check out the site for more information and videos that help explain the issues in plain English.
Each student is responsible for his or her conduct as it affects the University community. Academic dishonesty, in whatever form, is ultimately destructive of the values of the University. Furthermore, it is unfair and discouraging to the majority of students who pursue their studies honestly. Scholarly integrity is required of all members of the University. http://www.sfu.ca/policies/gazette/student/s10-01.html
TEACHING AT SFU IN FALL 2020
Teaching at SFU in fall 2020 will be conducted primarily through remote methods. There will be in-person course components in a few exceptional cases where this is fundamental to the educational goals of the course. Such course components will be clearly identified at registration, as will course components that will be “live” (synchronous) vs. at your own pace (asynchronous). Enrollment acknowledges that remote study may entail different modes of learning, interaction with your instructor, and ways of getting feedback on your work than may be the case for in-person classes. To ensure you can access all course materials, we recommend you have access to a computer with a microphone and camera, and the internet. In some cases your instructor may use Zoom or other means requiring a camera and microphone to invigilate exams. If proctoring software will be used, this will be confirmed in the first week of class.Students with hidden or visible disabilities who believe they may need class or exam accommodations, including in the current context of remote learning, are encouraged to register with the SFU Centre for Accessible Learning (firstname.lastname@example.org or 778-782-3112).