Selected topics of algorithms and computing in general. Topics include information theory, principles of data compression, arithmetic coding, JPEG and image quality, combinatoric optimization algorithms, branch and bound for TSP. The course is suitable to PhD students and advanced MSc students seeking deeper knowledge in algorithms.
Video lectures: ~20 hours
Discussions: 10 hours
Optional small project work.
Credits: 5 cp (with project), or 3 cp (w/o project).
Grading will be accept/fail based on participation activity and an oral examination. If needed, grading with scale 1-5 available by-request but might require written examination.
Video lectures and exercises that can be watched and made anytime. Discussion sessions (flipped learning principle), 1h each (max 2h if needed more).
Teachers: Pasi Fränti and Gulraiz I. Choudhary
Schedule: Starting from 13.1.2021
Wed 13.1.: MST to TSP
Wed 20.1.: Combinatoric optimization
Wed 20.1.: Local search for TSP
Wed 27.1.: Information theory, entropy, compression
Wed 3.2.: Arithmetic coding
Wed 10.2.: User similarity
Wed 10.2.: Extracting representative image
Wed 17.2.: Computer chess
Wed 24.2.: JPEG
Wed 24.2.: Image quality
MST to TSP
Local search for TSP
Basics of information theory
Algorithms in Chess
Design and Analysis of Algorithms (must be passed)
Passing the course will require:
Register via WebOodi
- Watching all videos
- Passing all exercises
- Oral examination (via Teams)
- Complete course project (5 cp variant) by deadline (28.3.2021)
Material will be delivered during the course.