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The website for the current lecture on convex optimization is here.

Surprisingly many real-world optimization problems can be reformulated as convex optimization problems. This convexity plays a central role in the computational tractability of a solution. The goals of this course are:

1. to provide the students with the necessary background to recognize optimization problems that can be reformulated as convex ones;
2. to study the duality theory of convex optimization from the point of view of conic programming, which includes as particular cases the linear programming (LP), semidefinite programming (SDP), second order cone programming (SOCP), and geometric programming (GP);
3. to review a variety of applications of convex optimization from various branches such as engineering, control theory, machine learning, robust optimization, and approximation algorithms for combinatorial problem;
4. finally, to understand algorithms for convex programming, in particular interior point methods, and to be able to use modern interfaces to pass optimization problems to solvers that implement these algorithms.

 An exercise session will be held every second week on Thursday.

Exceptionally, the lecture and exercises will be swapped in the first week of February: 

* Exercises on Monday, February 5;

* Lecture on Thursday, February 8.

Lecturer: Dr. Guillaume Sagnol

Assistant: Daniel Schmidt gen. Waldschmidt

If you participate to this course, please enter your contact information here (The password will be given in class):

www.thinfi.com/0zqp

Exercises will be given on week in advance. At the beginning of exercise sessions, check the exercises you've prepared. One student will be asked to explain his solution. You need 50% of all exercises checked to take the exam.

There will be an oral examination. You should not learn everything by heart, but rather know which result exists and be able to find it in your handout if needed. You will not be asked to prove results from the course, but rather to demonstrate your general understanding on convex optimization techniques, solve some new exercises, and show your modelling skills.

The oral examinations will take place on February 26 - February 27.

Please register for one exam slot at Daniel Schmidt's office (MA 524) during office hours, starting from January 22, 2PM. You also need to register for the exam at the Prüfungsamt, and bring us the yellow registration form no later than February 15 (last lecture).

All exams will take place in MA 518. Don't forget to bring your student ID!

There will be a handout, put online as and when the corresponding chapters are finished.

The course is mainly based on:

• Boyd, S., & Vandenberghe, L. (2004). Convex optimization. Cambridge university press.

Selected chapters are also based on the following references:

https://beta.mybinder.org/v2/gh/gsagnol/cvx_notebooks_TU_2017/master