Turnus of offer:
each summer semester
Course of studies, specific field and terms:
- Master CLS 2023 (compulsory), 1st, 2nd, or 3rd semester
- Master CLS 2016 (compulsory), 1st, 2nd, or 3rd semester
Classes and lectures:
- Optimization (exercise, 2 SWS)
- Optimization (lecture, 4 SWS)
- 20 Hours exam preparation
- 90 Hours in-classroom work
- 130 Hours private studies and exercises
Contents of teaching:
- Linear optimization (simplex method)
- Unconstrained nonlinear optimization (gradient descent, conjugate gradients, Newton method, Quasi- Newton methods, globalization)
- Equality- and inquality-constrained nonlinear optimization (Lagrange multipliers, active set methods)
- Stochastic methods for machine learning
- Students can model real-life problems as optimization problems.
- They understand central optimization techniques.
- They can explain central optimization techniques.
- They can compare and assess central optimization techniques.
- They can implement central optimization techniques.
- They can assess numerical results.
- They can select suitable optimization techniques for practical problems.
- Interdisciplinary qualifications:
- Students can transfer theoretical concepts into practical solutions.
- They are experienced in implementation.
- They can think abstractly about practical problems.
- Written or oral exam as announced by the examiner
Is requisite for:
Responsible for this module:
- J. Nocedal, S. Wright: Numerical Optimization - Springer
- F. Jarre: Optimierung - Springer
- C. Geiger: Theorie und Numerik restringierter Optimierungsaufgaben - Springer
Prerequisites for attending the module:
- None (Familiarity with the topics of the required modules is assumed, but the modules are not a formal prerequisite for attending the course).
Prerequisites for the exam:
- Preliminary examinations can be determined at the beginning of the semester. If preliminary work has been defined, it must have been completed and positively assessed before the first examination.
- MA4030-L1: Optimization, written examination (90min) or oral examination (30min) as decided by examiner, 100% of final mark
Variant of MA4030, MA4030-KP08 for students who did not attend a course on optimization in their Bachelors program.
Letzte Änderung: 14.12.2021