PULS
Foto: Matthias Friel
Prerequisites: Programming skills in at least one language. A course in basic numerical analysis. Recommended: some knowledge in numerical linear algebra.
Written or oral exam at the end of the semester. This course carries 9 Credits.
Course content:
Unconstrained optimisation: Intro, Newton method, Line search methods, Trust region methods, quasi-Newton methods,
Constrained optimisation: Optimality conditions, Method of Lagrange multipliers
Large Scale systems: Conjugate Gradient methods, Krylov methods, inverse problems.
Final year BSc students in Mathematics. MSc Students in Mathematics.
Should also be accessible for MSc Data Science and Lehramt (Education) if they have the prerequisites.
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