ECGR 4115: Convex Optimization and AI Applications
University of North Carolina, Charlotte
Focuses on the theory and the algorithmic aspects of convex optimization. Topics include: convex sets, convex functions, and convex optimization problems; duality theory and optimality conditions; algorithms for solving convex problems; use of numerical tools to solve problems; and, if time permits, non-convex optimization problems.� Also� discussed are applications of the materials to engineering topics such as signal processing, control, robotics, machine learning, statistics, and related engineering problems.
Average GPA: 2.58
Grade distribution records: 94 students across 4 terms.
Grade distribution
| Grade | Students | Percent |
|---|---|---|
| A | 24 | 25.5% |
| B | 20 | 21.3% |
| C | 25 | 26.6% |
| D | 11 | 11.7% |
| F | 4 | 4.3% |
| W | 9 | 9.6% |
Based on 94 student grade records across 4 terms and 2 professors.
Instructors
- Ahmed Arafa 53 students, Average GPA 2.16
- Dipankar Maity 41 students, Average GPA 3.07