Intended audience: Ph.D. students

Outline: A fast-paced introduction to Convex Analysis, directed by end-goals in Optimization. Part 1 of this course is taught by E.J. Balder, and part 2 (which starts on 8-10) will be taught by J. Brinkhuis.

Prerequisites: Knowledge of Advanced Calculus

Main subjects part 1: Convex sets, separation theorems, convex functions, subgradient calculus, Kuhn-Tucker theorem, generalized gradients.

Syllabus

Distributed on 10-9: Notes 1: On Subdifferential Calculus.

Distributed on 1-10: Notes 2: Lagrangian Duality and Perturbational Duality.

Course material:

Homework assignments: Set of homework problems. Make precisely 8 out of the 12 problems. You can jointly turn in with at most one other student. Good luck!