Convex Optimization

WS 2017/18

Lecturer: Prof. Dr.-Ing. C. Ebenbauer
Credits: 3V/1U


Prof. Dr.-Ing. Christian Ebenbauer


Zoltan Tuza

Time and place (3h lecture + 1h exercise)

Wednesdays: 9:45-11:15 in V 9.41
Thursdays: 14:00-16:00 in V 9.41
First lecture: October 25, 2017

Course description

Over the past two decades, convex optimization has become an important tool in many areas of engineering and applied sciences, such as systems theory and control, mechanics, signal processing, communication, combinatorics and graph theory, machine learning, operations research, electronic circuit design and biology. This course gives an introduction to the theory and application of convex optimization. The software used in the course is Matlab in combination with YALMIP. Some of the covered topics are:

  • Convex sets and functions
  • Optimality conditions
  • Conic programming (LP,CQP,SDP)
  • Duality theory
  • Numerical algorithms
  • Applications and projects

The overall goal of the course is to learn how to use and assess convex optimization techniques in order to solve optimization problems. We will also highlight the broad range of applications where these techniques can be applied.


No specific course prerequisites are required. The course is given in English.

Additional information, exercises and further course material is avaible on the ILIAS-page of the course.



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