Optimization Models and Applications
Instructors: A. Bayen, L. El Ghaoui
This course offers an introduction to optimization models and their applications, ranging from machine learning and statistics to decision-making and control, with emphasis on numerically tractable problems, such as linear or constrained least-squares optimization.
The course covers two main topics: practical linear algebra and convex optimization.The image on the left shows a graph of the Senators in the 2004-2006 US Senate, that is obtained by solving a specific optimization problem involving the estimation of covariance matrices with sparsity constraints. (For more details, see here.)
Tentative schedule: here.
Practical information: here.
Final exam: 12/14/18, 8-11AM.