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| Optimization Models in Engineering -- Electrical Engineering (EL ENG) 227AT [4 units] | ||||
| Course Format: Three hours of lecture and one hour of discussion per week. | ||||
| Prerequisites: Mathematics 54 or equivalent or consent of instructor. | ||||
| Credit option: Students will receive no credit for Electrical Engineering 227AT after taking Electrical Engineering 127. | ||||
| Description: 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. | ||||
| (SP) El Ghaoui |
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| Introduction to Convex Optimization -- Electrical Engineering (EL ENG) C227A [4 units] | ||||
| Course Format: Three hours of lecture, one hour of discussion, and two hours of laboratory per week. | ||||
| Prerequisites: Mathematics 54 and Statistics 2 or equivalents. | ||||
| Description: Convex optimization is a class of nonlinear optimization problems where the objectives to be minimized, and the constraints, are both convex. Contrary to the more classical linear programming framework, convex programs often go unrecognized, and this is a pity since a large class of convex optimization problems can now be efficiently solved. In addition, it is possible to address hard, non-convex problems (such as "combinatorial optimization" problems) using convex approximations that are more efficient than classical linear ones. The course covers some convex optimization theory and algorithms, and describes various applications arising in engineering design, machine learning and statistics, finance, and operations research. The course includes laboratory assignments, which consist of hands-on experience. Also listed as Industrial Engin and Oper Research C227A. | ||||
| (F,SP) El Ghaoul, Wainwright |
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