FRT225F

Temporary

Large-scale Convex Optimization

7.5

Third-cycle course

7161 (Automatic Control)

2020-11-13

Professor Thomas Johansson

English

If sufficient demand

The goal of the course is to give students the tools and training to recognize convex optimization problems that arise in applications. We present the basic theory of such problems, concentrating on results that are useful in algorithms for numerically solving the problems. The course will give the students a thorough understanding of how such problems are solved and give them experience in solving them, with the aim of giving the students the background required to use the methods in their own research.

Have knowledge about theory for convex sets, convex functions, duality, and algorithm convergence
Understand how application problems can be formulated as convex optimization problems and how they are solved
Have demonstrated understanding of how efficient algorithms for large-scale problems are implemented and work

Demonstrate the ability to evaluate if an optimization problem is convex
Formulate convex optimization problems in a standardized manner that is suitable for algorithms
Be able to implement and apply a suitable algorithm for a given convex optimization problem and prove its convergence

Lectures

Exercises

Written exam

Oral exam

Written assignments

Written or oral exam and written assignments during course.

Failed, pass

 

Material developed by teacher.

FRT225F

2020-11-13

Professor Thomas Johansson