Optimization ((3 Units))

Catalog description

Prerequisite: Permission of department. Topics include convexity, convex optimization problems, Lagrangian duality, optimality conditions and optimization in machine learning. Algorithmic topics will include the gradient descent and its variants, Newton’s and quasi-Newton methods. Applications will emphasize topics in data science.