Course description:
This course intends to provide a comprehensive insight into numrical methods for solving both unconstrained and constrained optimization problems. Although the focus is on computational methods,
theoretical properties of particular optimization problems and the related solution methods are addressed. Topics covered by this course include inter alia:
- Steepest descent method
- Newton's method and variants
- Methods for nonlinear Least-Squares
- Penalty and Barrier methods
- Interior-point methods
Prerequirements:
Linear Algebra
Analysis
Basic programming skills (R, Python, MatLab, or similar)
Preliminary meeting:
Dates:
Wed 08-10 (Lecture)
Thu 16-18 (Lecture)
Fr 12-14 (Exercise)
Contact:
Julian.Wagner@stat.uni-muenchen.de
- Teacher: Cornelia Fütterer
- Teacher: Julian Wagner