Week 2: Unconstrained optimization

DATA 442/642 · Week 2

Module 1 — Unconstrained optimization

Notes

• 2.1 Introduction to Optimization(slides)
• 2.2 Unconstrained Methods(slides)
• 2.3 Second-Order Methods(slides)

Labs

• Lab 2: Gradient Descent and Newton(PDF)

Additional

• 2. Eigenpairs and PSD matrices(PDF)
• Optimization methods(PDF)
• 3. Gradient descent and Newton(PDF)

Discussion

• When does a local minimum fail to be global?
• What does a large condition number do to steepest descent?