Infotech Oulu Doctoral Program
Lecturer: Professor Jan Kybic, Faculty of Electrical Engineering, Czech Technical University, Prague, Czech Republic
Date: September 13-15, 2016
Credits: 3 ECTS (tentative)
Please register to the course by sending email to Neslihan Bayramoglu (Email: firstname.lastname(at)oulu.fi)
Day1, Sept 13
10:00-13:00, TS127, Lectures
13:00-14:00, Break
14:00-16:00, TS135, Exercises
Day2, Sept 14
9:00-12:00, TS127, Lectures
There will be a short break between lectures and exercises
12:00-14:00, TS135, Exercises
Day3, Sept 15
10:00-13:00, TS101, Lectures
13:00-14:00, Break
14:00-16:00, TS135, Exercises
Course Content
In this three days mini course, the students will learn about optimization algorithms for in multidimensional Euclidean spaces. It includes least squares problems, constrained optimization, linear programming, convex optimization, iterative algorithms for non-linear optimization, from gradient descent to second-order methods. We will briefly introduce also more recent algorithms such as interior methods and ADMM (alternative direction of multipliers). At the end of the course, students should have a good overview of existing algorithms for solving optimization problems and their capabilities and should be able to choose appropriate method for a given optimization task. The course will be supplemented by homeworks. Some of them will require programming in a language of their choice, such as Matlab, Python, or Julia.
More information: Janne Heikkilä, Neslihan Bayramoglu
Last updated: 8.2.2017