Computational Mathematics for Learning and Data Analysis - AA 2024/25

Optimization problems with arbitrarily complex functions, but only one variable: the other step towards completely general (unconstrained) optimization. Conditions for optimization to be at least possible. Global optimization and why it is hard. Local optimization to the rescue: efficient algorithms are possible, and the role of derivatives there (the more, the better).