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MATH 434 Optimization Theory with Applications to Machine Learning

MATH 434  Optimization Theory with Applications to Machine Learning  Units: 3.00  

Theory of convex sets and functions; separation theorems; primal-duel properties; geometric treatment of optimization problems; algorithmic procedures for solving constrained optimization programs; engineering and economic applications.

Requirements: Prerequisite (MATH 110 or MATH 111 or MATH 212) and MATH 281.  
Offering Faculty: Faculty of Arts and Science  

Mathematics and Statistics

The Department of Mathematics and Statistics is located in its own building, Jeffery Hall. Graduate students are provided with study space in Jeffery Hall and most classes and seminars are scheduled in the building.

Mathematics and Statistics (MATH)

The department offers a selection of courses from the following list each academic year.  Course offerings for the current academic year can be found on the  Department of Mathematics and Statistics website . 

Mathematics – Major (Science) – Bachelor of Science (Honours)

Subject:  Administered by the Department of Mathematics and Statistics. Plan:  Consists of 60.00 units as described below. Program:  The Plan, alone, or in combination with a Minor in another subject, and with sufficient electives to total 120.00 units, will lead to a Bachelor of Science (Honours) Degree.