Mathematical Optimization
Durham
Engineering&Physical Sciences::Mathematics&Statistics
Credits: 4.0
Class Size: 10
Term:
Spring 2024
-
Full Term (01/23/2024
-
05/06/2024)
CRN:
53552
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 is required prior to taking this course.
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Prerequisite(s): MATH 426 or MATH 426H
Equivalent(s):
CS 757
Classes not allowed in section: Freshman, Sophomore
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 |
| 5/15/2024 | 5/15/2024 | W | 10:30am - 12:30pm | KING N113 |
