14083 - Special Topics of Convex Optimization Modulübersicht

Module Number: 14083
Module Title:Special Topics of Convex Optimization
  Spezielle Themen der konvexen Optimierung
Department: Faculty 1 - Mathematics, Computer Science, Physics, Electrical Engineering and Information Technology
Responsible Staff Member:
  • Prof. Dr. rer. nat. habil. Wachsmuth, Gerd
Language of Teaching / Examination:English
Duration:1 semester
Frequency of Offer: On special announcement
Credits: 8
Learning Outcome:After successfully completing the module, students have in-depth knowledge in the field of convex optimization. They are able to create and evaluate different formulations of a problem. They also are able to select and evaluate suitable methods.
Contents:Topics from the field of convex optimization, e.g.
  • Convex subdifferential
  • Duality theory 
  • Methods 
  • Maximum monotone operators
Recommended Prerequisites:Knowledge of the content of the modules
  • 13392: Differenzierbare Optimierung or 14356 Differentiable Optimization
  • 13844: Functional Analysis
Mandatory Prerequisites:None
Forms of Teaching and Proportion:
  • Lecture / 4 Hours per Week per Semester
  • Exercise / 2 Hours per Week per Semester
  • Self organised studies / 150 Hours
Teaching Materials and Literature:
  • Bauschke, Combettes: Convex analysis and monotone operator theory in Hilbert spaces, 2011
  • Clason, Valkonen, Introduction to nonsmooth analysis and optimization, 2020
Module Examination:Final Module Examination (MAP)
Assessment Mode for Module Examination:
  • Oral examination, 30 min. OR
  • Written examination, 180 min. (with high number of participants)
In the first lecture it will introduced, if the examination will organized in written or oral form.
Evaluation of Module Examination:Performance Verification – graded
Limited Number of Participants:None
Part of the Study Programme:
  • no assignment
Remarks:
  • Study programme Mathematics M.Sc.: Compulsory elective module in complex „Optimization“
Module Components:
  • Lecture: Special Topics of Convex Optimization
  • Exercise to the lecture
  • Related examination
Components to be offered in the Current Semester:
  • no assignment