This course will cover the fundamentals of convex optimization with a strong focus on finite dimensional search spaces. It covers theory, algorithm and applications.
The syllabus contains: convex sets, convex functions, optimization problems, subdifferential calculus (subgradients), optimality conditions in convex or differentiable optimization with equality and inequality constraints, duality theory. The last part is an introduction to the optimal control of ordinary differential equations.
