Convex optimization

This is a 4th year course about continuous (mainly convex) optimization.

The course is in two part:

• Optimization under uncertainty through dynamic programming: 2 class and a project over the semester
• Continuous optimization in three part
  • convex analysis and optimization theory (4 classes)
  • classical algorithms (3 classes)
  • more advanced materials (3 classes)

Documents

• Handout slides
• Reference book [BV] in the slides

• Another reference [JCG - French]

• Project to be done by pair for the 28/04/2022.
• DM 23 to be returned on 12/05

• A notebook to get a hand on julia.

• DM 22- with answers
• DS 22- with answers
• DM 21- with answers

• DS 21- with answers

• Short answers to some exercises

Timeline

01/03/24 - Markov chain and Dynamic Programming

slides Exercises

08/03/24 - Dynamic Programming in infinite horizon

slides Hands on (pdf) Hands on (notebook)

15/03/24 - Convex analysis 1

slides Exercises

22/03/24 - Convex analysis 2

slides Exercises

29/03/24 - Optimality conditions

slides Exercises

12/04/24 - Duality

slides Exercises

26/04/24 - Algorithm’s zoology

slides Exercises

03/05/24 - Gradient and Newton’s algorithms

slides slides

17/05/24 - Practical work on algorithms

Hands on (notebook)

24/05/24 - Constrained optimization

slides

31/05/24 - Interior points methods

slides Hands on (notebook)

07/06/24 - Stochastic Gradient

slides

14/06/24 - Exam