INMA2460: Nonlinear Optimization

Goals of the course

Consists of four Chapters composed by three lectures each, and of two Exercises.
Each Exercise suggests a numerical study of some optimization methods introduced in Chapter 2 and Chapter 3.
For each exercise student can get up to 5 points.
Written exam is given in the end of semester. It consists of 4 questions, one for each chapter (5 points).
For Chapters 2 and 3, the student can use either the points for the questions, or for corresponding excercises.

Chapter 1: General nonlinear optimization	Lecture 1 (S1: Feb 01): Introduction Lecture 2 (S2: Feb 08): Local methods in Nonlinear Optimization Lecture 3 (S3: Feb 15): First-order methods. Constrained Optimization
Chapter 2: Smooth convex optimization (by O.Devolder)	Lecture 4 (S4: Feb 22): Minimization of smooth functions Lecture 5 (S5: Mar 01): Optimal methods. Minimization over simple sets. Lecture 6 (S6: Mar 08): Minimization with Smooth functional components.
Chapter 3: Non-smooth convex optimization	Lecture 7 (S7 Mar 15): General convex functions Lecture 8 (S9: Mar 29): Nonsmooth minimization methods Lecture 9 (S10: Apr 05): Methods with complete data
Chapter 4: Structural optimization. Interior-point methods	Lecture 10 (S11: Apr 26): Self-concordant functions Lecture 11 (S12: May 03): Self-concordant barriers Lecture 12 (S13: May 10): Applications of Structural Optimization

Ref: Yu.Nesterov. Introductory lectures on Convex Optimization. A Basic Course. Kluwer, Boston, 2004.