Prof. Dr. Frank Vallentin
Übungsaufgaben und die Abschlussklausur können wahlweise in Englisch oder in Deutsch bearbeitet werden.
The course will be organized in English. Exercises and the final exam can be submitted either in German or in English.
In modern „Convex Optimization“ the theory of semidefinite optimization plays a central role. Semidefinite optimization is a generalization of linear optimization, where one wants to optimize linear functions over positive semidefinite matrices restricted by linear constraints. A wide class of convex optimization problems can be modeled using semidefinite optimization. On the one hand, there are algorithms to solve semidefinite optimization problems, which are efficient in theory and practice. On the other hand, semidefinite optimization is a tool of particular usefulness and elegance.
The aim of this course is to provide an introduction to the theory of semidefinite optimization, to algorithmic techniques, and to mathematical applications in combinatorics, geometry and algebra.
Großer Hörsaal der Mathematik (Raum 203)
Note: The lecture on Friday, Dec 21, will not take place. Please study this week’s material (Chapter 7, § 5) on your own. It will be relevant for the oral exam.
Please see the Exercises-page for more information.
Wednesday 30.01.2019, 12.00-13:30 (Raum 203 MI)
Results of the Exam
Post-exam review on Monday, Feb. 4, 14:30-15:30 in our offices (Weyertal 80).
Example Questions for Oral Exams
Appointments for the Oral Exams
You can find the file with the appointments here (If you cannot remember the password, send us a mail or come to our office hours).
If you need a Signature for the registration form from us, this can also be obtained from Annette Koenen (Weyertal 80, ground floor on the right).
To get an idea of how an exam could look like, here is an exam from 2016. Of course the material is not identical so this should not be taken as a definitive selection of topics for exam questions.