Lectures related to Convex curve

Discusses interpreting convergence plots in optimization, identifying bugs based on convergence rates, and understanding optimization algorithms.

Introduces Fenchel conjugation, exploring its properties, examples, and applications in nonsmooth optimization problems and minimax formulations.

Covers the KKT conditions for optimization with constraints, essential for solving constrained optimization problems efficiently.

Explains gradient descent for optimization and how to find the direction towards the solution by minimizing distances.

Covers faster gradient descent methods and projected gradient descent for constrained optimization in machine learning.