ECE490: Introduction to Optimization (Spring 2022)
Course Information
Course DescriptionThis is a senior/first year graduatelevel course on optimization. Topics include necessary and sufficient conditions for local optima; characterization of convex sets and functions; unconstrained optimization, gradient descent and it variants; constrained optimization and the gradient projection method; optimization with equality and inequality constraints, Lagrange multipliers, KKT conditions; penalty and barrier function methods; weak and strong duality and Slater conditions; augmented Lagrangian methods; subgradient methods; proximal gradient descent; applications. TextbookThe recommended textbook is Nonlinear Programming by D. Bertsekas (Edition 3). We will closely follow the lecture notes and slides distributed via email. Grading
