MATH 857 (01R) - Mathematical Optimization for Applications

Mathematical Optimization

Durham   Engineering&Physical Sciences :: Mathematics&Statistics
Online Course Delivery Method: Scheduled meeting time, Remote Section, Online (no campus visits), EUNH
Credits: 3.0
Term: Spring 2021 - Full Term (02/01/2021 - 05/11/2021)
Grade Mode: Letter Grading
Class Size:   2  
CRN: 56992
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. Students are required to have programming proficiency in MATLAB, R, Java, C, Python, and mastery of Calculus II.
You must sign up in the Dept Office before registering through WEBCAT.
Equivalent(s): CS 857
Instructors: Marek Petrik

Times & Locations

Start Date End Date Days Time Location
2/1/2021 5/11/2021 MWF 9:40am - 11:00am ONLINE

Booklist

Nonlinear Programming: 3rd Edition by Dimitri P. Bertsekas