MATH7237 (Theory of Optimization) course reviews and ratings at Northeastern (NEU). Compare professors with RateMyProfessor reviews.
Focuses on the rigorous mathematical theory pertaining to finite-dimensional optimization including convex analysis, optimality conditions, Lagrangean duality, and convergence rates of optimization algorithms. Topics include convex sets, cones, polar cones, dual cones, extreme points, polyhedra, convex functions, epigraphs, subgradients, convex conjugation, Fenchel-Moreau theorem, necessary and sufficient conditions for optimality, tangent cones, constraint qualification, Slater’s condition, Karush-Kuhn-Tucker conditions, Lagrange multipliers, primal problems and dual problems, semidefinite programming, Farkas’ lemma, theorems of the alternative, gradient descent, Newton’s method, and convergence rates.
Data updated October 2026.