TEACHING
CONVEX OPTIMIZATION AND MODELING
Sommersemester 2010
GENERAL INFORMATION
Convex optimization is a special class of mathematical optimization. Linear and quadratic programming problems are special cases. Convex optimization problems arise quite naturally in many application areas like signal processing, machine learning, image processing, communication and networks and finance etc.
The course will have as topics convex analysis and the theory of convex optimization such as duality theory, algorithms for solving convex optimization problems such as interior point methods but also the basic methods in general nonlinear unconstrained minimization, and last but not least several applications where the modeling part, that is the transition from the problem to the formulation of an optimization problem is discussed.
The course requires a good background in linear algebra and calculus, but no prior knowledge in optimization is required. The course will follow to large extent the book of Boyd and Vandenberge on "Convex Optimization" and can be seen as complementary to the core lecture "Optimization" which will also takes place during the summer semester.
Students who intend to do their master thesis in machine learning are encouraged to take this course.
Type: Advanced course (Vertiefungsvorlesung), 6 credit points
LECTURE MATERIAL
The course follows in the first part the book of Boyd and Vandenberghe.
The practical exercises will be in Matlab and will make use of CVX.
SLIDES AND EXCERCISES
LITERATURE AND OTHER RESOURCES
- The lecture will be based on the following book:
S. Boyd and L. Vandenberghe: Convex Optimization, Cambridge University Press, (2004).
The book is freely available - Complementary book: D. P. Bertsekas: Nonlinear Programming, Athena Scientific, (1999).
- Other resources:
- Matlab is available on cip[101-114] and cip[220-238].studcs.uni-sb.de, gpool[01-27].studcs.uni-sb.de
The path is /usr/local/matlab/bin.
For the sun workstations you have to select in the menu Applications/studcsApplications/Matlab
Access from outside should be possible via ssh: ssh -X username@computername.studcs.uni-sb.de - Matlab tutorial by David F. Griffiths
- Matlab is available on cip[101-114] and cip[220-238].studcs.uni-sb.de, gpool[01-27].studcs.uni-sb.de
NEWS
Dates for the oral exam: 30.7. and 6.8. Please write me an email with the dates where you would be available and I schedule the exams.
TIME AND LOCATION
Lecture: We, 10-12, E1 3, HS III
Exercises: Fr, 16-18, E2 4, Room 216
EXAMS AND GRADING
Exams: End-term: Re-exam:
Grading:
- 50% of the points in the exercises are needed to take part in the exams.
- An exam is passed if you get at least 50% of the points.
- The grading is based on the better result of the end-term and re-exam.
- Exams can be oral or written (depends on the number of participants).
LECTURER
Office Hours: Mo, 16-18, Th, 16-18
Organization: Shyam Sundar Rangapuram