Convex Optimization

Acquire a basic understanding of mathematical optimization and its applications.

This lesson will cover the following topics:

     - Unconstrained extrema: the concept of convexity, optimality conditions, descent methods, separable functionals, stochastic gradient

     - Extremes with constraints: strong and weak formulations, constrained extremes, Lagrange multipliers, and implementation using the Newton method. KKT conditions, duality, Uzawa. Linear programming

     - Introduction to Mathematics Education

     - Some areas of application:

Coursework from L1, L2, and the first semester of L3, specifically:

- HAX404X Topology of^{R^n} and Functions of Several Variables

- HAX502X Differential Calculus and Differential Equations

Recommended prerequisites: first semester of the third year of a bachelor's degree program

Hourly volumes:

            CM: 18

            TD: 15

            TP: 12

            Land: -