Instructors: Professors Pablo Parrilo (firstname.lastname@example.org), Ankur Moitra (email@example.com)
Schedule: Lectures, MWF1 room 4-370; Recitations TR 10, 11, 12, 1, 2, 3, room 2-146
Unified introduction to linear algebra and optimization, their interconnections, and applications throughout science and engineering. Specific topics include vectors, matrices, eigenvalues, singular values, least-squares, convex optimization, linear/quadratic programming, gradient descent, Newton’s method. Viewpoint will emphasize conceptual, geometric, and computational aspects. Applications from many domains, including networks, signal processing, and machine learning.
Relation to 18.06: This course will count towards the linear algebra requirement for math majors! Also, since the material will overlap substantially with 18.06 it is strongly advised that you do not take it if you have already taken 18.06. They are not classified by the registrar as classes with essentially similar content, but individual majors (e.g. math and eecs) may treat them as such