Resources

Officially Supported Resources

The following textbooks are highly recommended resources for the course.

1. Calafiore, Giuseppe and El Ghaoui, Laurent. Optimization Models.
2. Boyd, Stephen, and Vandenberghe, Lieven. Convex Optimization.

In addition, the staff from Spring 2023 wrote a course reader which follows the lectures; these notes have been augmented by every set of course staff since then.

Other Useful Resources

The following are resources that course staff thinks are helpful, but we do not want to officially support. They might be helpful to learn the material, but also might have bugs, etc. The list will expand periodically throughout the semester as we collect more resources.

1. Petersen, Kaare and Pedersen, Michael. Matrix Cookbook.
2. Bubeck, Sebastien. Convex Optimization: Algorithms and Complexity.
3. Varaiya, Pravin. Lecture Notes on Optimization.

Past Exams