CSC466H1: Numerical Methods for Optimization Problems



Numerical methods for unconstrained optimization problems, in particular line search methods and trust region methods. Topics include steepest descent, Newton's method, quasi-Newton methods, conjugate gradient methods and techniques for large problems. This course will normally be offered every other year.

NOTE: Students not enrolled in the Computer Science Major or Specialist program at A&S, UTM, or UTSC, or the Data Science Specialist at A&S, are limited to a maximum of 1.5 credits in 300-/400-level CSC/ECE courses.
Distribution Requirements
Breadth Requirements
The Physical and Mathematical Universes (5)
Mode of Delivery
In Class