CO 367 Nonlinear Optimization, Fall 2021

Undergraduate course, Department of Combinatorics and Optimization, University of Waterloo, 2021

An introductory course to the mathematics of nonlinear optimization. Necessary and sufficient optimality conditions for unconstrained and constrained problems. Convexity and its applications. Computational algorithms and their analysis. Application to machine learning.

Topics:

  1. Introduction and Unconstrained optimization
  2. Convex sets and convex functions.
  3. Duality theory
  4. Algorithms for unconstrained optimization.
  5. Trust region methods.
  6. Least squares optimization.
  7. Constrained Optimization.
  8. Algorithms for constrained optimization.
  9. Application to Deep Learning

======

Course Syllabus

Course Notes