Lecture Plan
The following plan is preliminary and subject to change.
| Week | Topic | Lecture Notes | N&W | Additional Notes |
|---|---|---|---|---|
| 2 | Introduction | Lecture 1 Lecture 2 | Chapters 1&2 | Minimizers |
| 3 | Convex Functions, Optimality Conditions | Lecture 3 Lecture 4 | Chapters 1&2 | Convex Functions |
| 4 | Descent Methods | Lecture 5 | Chapter 2.2 | |
| 5 | Inexact line search methods; Wolfe conditions | Lecture 6 Lecture 7 | Chapter 3.1 | |
| 6 | Example steepest descent; Sufficient decrease and backtracking; Convergence rates | Lecture 8 | Chapters 3.1-3.3 | |
| 7 | Newton Method Quasi-Newton Methods | Lecture 9 Lecture 10 | Chapter 3.3 Chapter 2.2 | |
| 8 | No classes this week - Work on Project | |||
| 9 | SR1-method Least Squares problems | Lecture 11 Lecture 12 Slides (Video of Lecture 12 can be found on Blackboard under "Learning Materials") | Chapter 3.3 Chapters 10.1-10.4 | |
| 10 | DFP Method BFGS Method Conjugate Gradient Method Submit the Project | Lecture 13 Lecture 14 | Chapters 6.1-6.2 | |
| 11 | Conjugate Gradient Method Constrained optimization: First order optimality conditions | Lecture 15 Lecture 16 | Chapter 5.1 Chapters 12.1-12.3 | |
| 12 | Constrained optimization: Second-Order Optimality Conditions | Lecture 17 Videos from Lecture 17 and 18 are available in BB in the Panopto folder | ||
| 13 | Penalty Method | Lecture 19 (Slides without comments) Lecture 19 (Slides with comments) | Chapters 17.1-17.2 | |
| 14 | Linear Programs; Duality | Lecture 20 (Video is available BB) | ||
| 15 | Easter Holidays - No teaching | |||
| 16 | Vector Optimization Repetition and exam preparation Project grade ready, feedback on project | Lecture 21 Lecture 22 | Vector Programming |