Advanced Topics in Algorithms (3-5 cp) 3621647


Course description

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.

Content

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.

Format of teaching

Video lectures and exercises that can be watched and made anytime. Discussion sessions (flipped learning principle), 1h each (max 2h if needed more).

Teacher and schedule

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

Exercises

Exercises

Material:

MST to TSP
Combinatoric optimization
Local search for TSP
Basics of information theory
User similarity
Extracting images
Genetic algorithms
Algorithms in Chess
JPEG
Image quality

Preliminary knowledge

Design and Analysis of Algorithms (must be passed)

Exams

Format: Oral
Grading: Passed/Failed
Passing the course will require:

Register via WebOodi

Literature

Material will be delivered during the course.