Mathematical Optimization
Durham
Engineering&Physical Sciences::Computer Science
Credits: 4.0
Class Size: 7
Term:
Spring 2024
-
Full Term (01/23/2024
-
05/06/2024)
CRN:
52878
Grade Mode:
Letter Grading
This course introduces the foundations of mathematical optimization and reinforces them via applications. The content includes convex optimization, first and second-order methods, constrained problems, duality, linear and quadratic programming, as well as discrete and non-convex optimization. Applications will focus on machine learning methods but also include problems from engineering and operations research. Programming proficiency in MATLAB, R, Java, C, Python, or equivalent required.
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Cross Listed With :
CS 857 (01)
Prerequisite(s): MATH 426
Equivalent(s):
MATH 757
Only listed colleges in section: Engineering&Physical Sciences
Instructors:
Marek Petrik
Times & Locations
| Start Date | End Date | Days | Time | Location |
|---|---|---|---|---|
| 1/23/2024 | 5/6/2024 | MWF | 10:10am - 11:00am | KING N113 |
| Final Exam5/15/2024 | 5/15/2024 | W | 10:30am - 12:30pm | KING N113 |
