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I teach the lecture jointly with Martin Loebl. I have the continuous part, whereas Martin Loebl the discrete part.
Schedule of lectures:
| 19.2. |
Unconstrained optimization: optimality criteria of the first and second order, illustration on the least square problem. Convex sets.
[chapter 2, sections 3.1-3.2] |
| 26.2. |
Convex functions: first and second order characterization, chain rules.
Convex optimization: basic properties of the optimal solutions, characterization of optimality. [sections 3.3-3.4, 4.1] |
| 5.3. |
Quadratic optimization: formulation, complexity, the convex case, two examples.
Convex optimization and complexity: the idea of the ellipsoid method for polynomial-time problems and an example of copositive optimization as a hard problem. [sections 4.2, 4.5] |
| (plan) 12.3. |
Convex cone programming: formulation, convex cones, dual cones, the dual problem, weak and strong duality.
Special cases: Cone quadratic programming and semidefinite programming. [section 4.4] |
Literature:
