Nonlinear Optimization, 9.0 credits
Nonlinear Optimization, 9.0 hp
6FMAI19
Course level
Third-cycle EducationDescription
Contact the examiner if interested.
https://courses.mai.liu.se/FU/6FMAI19/
Current and recently held PhD courses at the Department of Mathematics can be found here: https://liu.se/artikel/doktorandkurser-vid-matematiska-institutionen
Contact
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Yurii Malitskyi
Examiner
Entry requirements
Calculus, linear algebra.
Contents
First-order methods (unconstrained and constrained optimization, accelerated methods, stochastic methods, nonsmooth methods, non-Euclidean methods), saddle point problems, variational inequalities, second-order methods.
The goal of the course is to give a broad overview of various optimization algorithms. Students will be introduced to popular modern optimization techniques in nonlinear optimization and better understand the need for optimization in machine learning, engineering, and data science.
Educational methods
One lecture per week.
Examination
One scribed lecture, homework assignments.
Grading
Two-grade scaleCourse literature
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- Beck. First-Order Methods in Optimization, 2017.
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- Bertsekas. Convex optimization algorithms, 2015.
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- Boyd, L. Vandenberghe. Convex optimization, 2015.