Logistics

Instructors:

• Somayeh Sojoudi (sojoudi at berkeley), OH: Tue 2-3pm, 5114 Etcheverry Hall, ending October 8.

• Laurent El Ghaoui (elghaoui at berkeley), OH: Tue 2-3pm, 421 Sutardja Dai Hall, starting October 15.

Teaching assistant: Armin Askari, OH: 9-10am Wednesday, Cory 367.

Material: Main references are

• Part I: Convex optimization (S. Boyd and L. Vandenberghe), Linear and nonlinear programming (D. Luenberger), Nonlinear programming (D. Bertsekas).

• Part II: Robust optimization (A. Bental, L. El Ghaoui, A. Nemirovski).

• Background material: the livebook here (Registration is free.) This class assumes a strong knowledge of linear algebra, as covered in EECS 127 / 227AT.

Discussion sections: W 10-11 (204 Wheeler) and W 11-12 (108 Wheeler).

Homeworks: there will be about 5 Homeworks, which require the use of Matlab or Python.

Exams: There is a midterm (on Oct. 15), no final and a project.

Project: You are encouraged to form a project team of 4 (no less than 3, and 5 max). More details on projects here.

Grading: 40% homework, midterm (30%), project (30%).