This is a graduate level introductory course focusing on optimization fundamentals and their practical applications.

Slides (Fall 2023)

• 1 Introduction

• 2 Algebra background

• 3 Derivatives

• 4 Optimization problems

• 5 Single-variable optimization

• 6 Unconstrained optimization

• 7 Least squares

• 8 Constrained optimization

• 9 Convex optimization

• 10 Linear programs

• 11 Special classes of convex optimization

• 12 Duality

• 13 Dual based method

• 14 Neural networks