EE364B  Convex Optimization II
EE364B: Convex Optimization II (Stanford Univ.). Taught by Professor Stephen Boyd, this course concentrates on recognizing and solving
convex optimization problems that arise in engineering. Continuation of Convex Optimization I. Subgradient, cuttingplane, and ellipsoid methods.
Decentralized convex optimization via primal and dual decomposition. Alternating projections. Exploiting problem structure in implementation.
Convex relaxations of hard problems, and global optimization via branch & bound. Robust optimization. Selected applications in areas such as control,
circuit design, signal processing, and communications. Course requirements include a substantial project.
(from see.stanford.edu)
Lecture 01  Introduction, Subgradients 
Lecture 02  Subgradients (cont.) 
Lecture 03  Convergence Proof, Subgradient Methods, Linear Equality Constraints 
Lecture 04  Subgradient Method for Constrained Optimization, Convergence 
Lecture 05  Stochastic Programming, Localization and CuttingPlane Methods 
Lecture 06  Analytic Center CuttingPlane Method, Infeasible Start Newton Method Algorithm 
Lecture 07  ACCPM With Constraint Dropping, Ellipsoid Method 
Lecture 08  Recap: Ellipsoid Method, Primal Decomposition, Dual Decomposition 
Lecture 09  Recap: Primal Decomposition, Dual Decomposition 
Lecture 10  Decomposition Applications 
Lecture 11  Sequential Convex Programming 
Lecture 12  Recap: 'Difference Of Convex' Programming, Conjugate Gradient Method, Krylov Subspace 
Lecture 13  Recap: Conjugate Gradient Method and Krylov Subspace, Truncated Newton Method 
Lecture 14  Truncated Newton Method, L1Norm Methods 
Lecture 15  L1Norm Methods 
Lecture 16  Model Predictive Control 
Lecture 17  Stochastic Model Predictive Control, Branch and Bound Methods 
Lecture 18  Branch and Bound Methods 
References 
EE364B  Convex Optimization II
Instructors: Professor Stephen Boyd. Handouts. Assignments. Exams. This course concentrates on recognizing and solving convex optimization problems that arise in engineering.
