## EEOR E4650: Convex OptimizationProfessor Javad Lavaei, UC Berkeley, Teaching at Columbia University in Fall 2013
30% homework 25% midterm exam 45% course project
## DescriptionSyllabus: Convex sets and functions Convex optimization Duality Numerical algorithms Decomposition and distributed algorithms Linear matrix inequality Sum-of-squares technique Application in communications: TCP and congestion control Application in control: stability, robust control and optimal control Application in signal processing: compressed sensing Application in circuits: circuit design Application in power systems: optimal power flow
References: Main textbook: “ *Convex Optimization*” by Stephen Boyd and Lieven Vandenberghe (available online at http:www.stanford.edu*boyd*cvxbook/)Research papers
## Lecture NotesWeek 1: Overview and introduction (Chapter 1) Week 2: Convex sets and functions (Chapters 2-3) Week 3: Convex optimization (Chapter 4) Week 4: Conic optimization & examples (Chapter 4) Week 5: Duality theory (Chapter 5) Week 6: KKT conditions and midterm review (Chapter 5) Week 7: Numerical algorithms for unconstrained optimization (Chapter 9) Week 8: Primal-dual algorithm, distributed computation, optimization for communication networks (Chapters 10-11) Week 9: LMI formulation of stability and optimal control (LQR and LQG) Week 10: Optimization for power systems Week 11: Compressed sensing, summary of the course (materials: 1 and 2)
## Homework |