MATH347

Introduction to Continuous Optimization

Introduction to theory and algorithms of optimization in the continuous context. Topics may include: optimality conditions for unconstrained and constrained optimization problems, solutions to least squares problems, iterative methods for unconstrained optimization such as gradient descent and Newton’s method, convex sets and convex functions, convex duality, introduction to software tools.