Fall 2019
| Instructor |
Aria Nosratinia,
ECSN 4.504, Tel: 972-883-2894 |
| Time | Mon. Wed.. 11:30am-12:45pm |
| Place | ECSN2.112 |
| Textbook | Boyd and Vanderberghe, Convex Optimization Cambridge University Press. |
| The textbook is available from the UTD Bookstore, Off Campus Books, as well as Amazon (click on link to go to the book page), Barnes and Noble, and other sources. | |
| Tentative Grading Outline | class participation (10%), Homework (10%), Midterm (30%), Project (30%) Final Exam (20%) |
| Exam times: | Midterm Exam October 19, Final Exam Dec. 11 |
| Prerequisite | Undergraduate algebra, calculus, probability |
| Office Hours | Tue-Thu. 10:30am-11:20am |
| TA Information: | TBA |
This course concentrates on recognizing and solving convex optimization problems, with emphasis on problems in engineering. The objectives of the course are to give the student the tools and techniques to recognize convex optimization problems, present the basic theory of these problems, give the students a thorough understanding of how these problems are solved, and enable the students to use these results in their research. This course does not have any graduate-level pre-requisites, but a thorough understanding and mastery of undergraduate-level mathematical results from calculus and linear algebra is necessary for fully benefiting from this course.
Contents:
- Convex sets
- Convex Functions
- Convex Optimization Problems
- Duality
- Approximations and Fitting
- statistical estimation
- geometrical problems
- Unconstrained optimization
- Equality Constraints
- Interior point methods