|Optimization. - 16631 - MATH 560 - 001|
Line search methods including steepest descent, Newton's (and Quasi-Newton) methods. Trust region methods, conjugate gradient method, solving nonlinear equations, theory of constrained optimization including a rigorous derivation of Karush-Kuhn-Tucker conditions, convex optimization including duality and sensitivity. Interior point methods for linear programming, and conic programming.
Prerequisite: Undergraduate background in analysis and linear algebra, with instructor's approval
Associated Term: Winter 2018
Registration Dates: Apr 04, 2017 to Jan 23, 2018
Lecture Schedule Type
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