EE364A  Convex Optimization I
EE364A: Convex Optimization I (Stanford Univ.). Taught by Professor Stephen Boyd, this course concentrates on recognizing and solving
convex optimization problems that arise in engineering. Convex sets, functions, and optimization problems. Basics of convex analysis. Leastsquares,
linear and quadratic programs, semidefinite programming, minimax, extremal volume, and other problems. Optimality conditions, duality theory,
theorems of alternative, and applications. Interiorpoint methods. Applications to signal processing, control, digital and analog circuit design,
computational geometry, statistics, and mechanical engineering. (from see.stanford.edu)
Lecture 01  Introduction 
Lecture 02  Guest Lecturer: Jacob Mattingley, Convex Sets and Their Applications 
Lecture 03  Logistics, Convex Functions, Examples 
Lecture 04  Quasiconvex Functions, Examples, LogConcave and LogConvex Functions 
Lecture 05  Optimal and Locally Optimal Points, Convex Optimization Problem, Quasiconvex Optimization 
Lecture 06  LinearFractional Program, Quadratic Program 
Lecture 07  Generalized Inequality Constraints, Semidefinite Program (SDP) 
Lecture 08  Lagrangian, LeastNorm Solution Of Linear Equations, Dual Problem, Weak and Strong Duality 
Lecture 09  Complementary Slackness, KarushKuhnTucker (KKT) Conditions, Sensitivity, Duality 
Lecture 10  Applications: Norm Approximation, Penalty Function Approximation, LeastNorm Problems, etc. 
Lecture 11  Statistical Estimation, Maximum Likelihood Estimation 
Lecture 12  Geometric Problems 
Lecture 13  Linear Discrimination, Nonlinear Discrimination, Numerical Linear Algebra Background 
Lecture 14  Numerical Linear Algebra Background, Factorizations 
Lecture 15  Algorithm  Unconstrained Minimization 
Lecture 16  Unconstrained Minimization (cont.), Equality Constrained Minimization 
Lecture 17  Equality Constrained Minimization (cont.), InteriorPoint Methods 
Lecture 18  Logarithmic Barrier, Central Path, Barrier Method, Feasibility and Phase I Methods 
Lecture 19  InteriorPoint Methods, Barrier Method (Review), Generalized Inequalities 
References 
EE364A  Convex Optimization I
Instructors: Professor Stephen Boyd. Handouts. Assignments. Exams. This course concentrates on recognizing and solving convex optimization problems that arise in engineering.
