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. Least-squares,
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 06 - Linear-Fractional Program, Quadratic Program