AOE-5734: Convex Optimization
Description: Recognizing and solving convex optimization problems. Convex sets, functions, and optimization problems. Least-squares, linear, and quadratic optimization. Geometric and semidefinite programming. Vector optimization. Duality theory. Convex relaxations. Approximation, fitting, and statistical estimation. Geometric problems. Control and trajectory planning. Pre: Graduate standing.
Pathways: N/A
Course Hours: 3 credits
Sections Taught: 5
Average GPA: 3.55 (A-)
Strict A Rate (No A-) : 48.34%
Average Withdrawal Rate: 0.00%
| Mazen H Farhood | 2024 | 58.1% | 38.6% | 3.3% | 0.0% | 0.0% | 0.0% | 3.55 | 5 |