Mathematical-Optimization-MIPT

Homework assignments in mathematical optimization, MIPT, 2018-2019.

Fall 2018

I consistently received the best score among fellow students throughout the course.

Syllabus

1. Introduction. Convex sets and cones
2. Matrix calculus
3. Convex functions
4. KKT optimality conditions
5. Duality
6. Midterm
7. Introduction to numerical optimization and gradient descent
8. Beyond gradient descent: heavy ball, conjugate gradient and fast gradient methods
9. Stochastic first-order methods
10. Newton and quasi-Newton methods
11. Projected gradient method, Frank-Wolfe method and introduction to proximal methods
12. Linear programming problem
13. Semidefinite programming
14. Interior point methods and concept of self-concordance functions