Times

I established this course in the fall semester of 2016 and have also taught the class in the fall of 2018 and spring 2020. Given the high demand, I hope the class can be offered once per academic year.

Description

Nonlinear optimization problems arise in a wide range of applications, for example, in economics, physics, engineering, machine learning, and imaging. This introductory course covers a variety of relevant unconstrained and constrained optimization problems. While its emphasis is on theory, we will also discuss real-world applications and solve small-scale, smooth optimization problems numerically.

Prerequisites

Math 211, Math 221 or 321, Math 250, and CS 170

Literature

The primary textbook for the course is the following: Introduction to Nonlinear Optimization by A. Beck. Reading the textbook is not required, but it is recommended. I will provide lecture notes with detailed references for each lecture. You are not responsible for textbook material that is not covered in lecture.