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. Optimali…
Lecture by Professor Stephen Boyd for Convex Optimizations II (EE 364B) in the Stanford Electrical Engineering department. Professor Boyd's first lecture is on the course requirements and homework assignments.
Lecture by Professor Stephen Boyd for Convex Optimizations II (EE 364B) in the Stanford Electrical Engineering department. Professor Boyd continues subgradients.
Lecture by Professor Stephen Boyd for Convex Optimizations II (EE 364B) in the Stanford Electrical Engineering department. Professor Boyd covers subgradient methods.
Lecture by Professor Stephen Boyd for Convex Optimizations II (EE 364B) in the Stanford Electrical Engineering department. Professor Boyd lectures on subgradient methods for constrained problems.
Lecture by Professor Stephen Boyd for Convex Optimizations II (EE 364B) in the Stanford Electrical Engineering department. Professor Boyd introduces stochastic programing and the localization and cutting-plane methods.
Lecture by Professor Stephen Boyd for Convex Optimizations II (EE 364B) in the Stanford Electrical Engineering department. Professor Boyd lectures on the localization and cutting-plane methods and then moves into the Analytic center cutting-plane methods.
Lecture by Professor Stephen Boyd for Convex Optimizations II (EE 364B) in the Stanford Electrical Engineering department. Professor Boyd finishes his lecture on Analytic center cutting-plane method, and begins Ellipsoid methods.
Lecture by Professor Stephen Boyd for Convex Optimizations II (EE 364B) in the Stanford Electrical Engineering department. Professor Boyd introduces primal and dual decomposition methods.
Lecture by Professor Stephen Boyd for Convex Optimizations II (EE 364B) in the Stanford Electrical Engineering department. Professor Boyd concludes his lecture on primal and dual decomposition methods.
Lecture by Professor Stephen Boyd for Convex Optimizations II (EE 364B) in the Stanford Electrical Engineering department. Professor Boyd introduces a new topic, Decomposition Applications.
Lecture by Professor Stephen Boyd for Convex Optimizations II (EE 364B) in the Stanford Electrical Engineering department. Professor Boyd lectures on Sequential Convex Programming.
Lecture by Professor Stephen Boyd for Convex Optimizations II (EE 364B) in the Stanford Electrical Engineering department. Professor Boyd finishes his talk on Sequential Convex Programming and begins a lecture on Conjugate Gradient Methods.
Lecture by Professor Stephen Boyd for Convex Optimizations II (EE 364B) in the Stanford Electrical Engineering department. Professor Boyd continues his lecture on Conjugate Gradient Methods and then starts lecturing on the Truncated Newton Method.
Lecture by Professor Stephen Boyd for Convex Optimizations II (EE 364B) in the Stanford Electrical Engineering department. Professor Boyd continues his lecture on the Truncated Newton Method then moves into L1-Norm Methods for Convex-Cardinality Problems.
Lecture by Professor Stephen Boyd for Convex Optimizations II (EE 364B) in the Stanford Electrical Engineering department. Professor Boyd continues lecturing on L1 Methods for Convex-Cardinality Problems.
Lecture by Professor Stephen Boyd for Convex Optimizations II (EE 364B) in the Stanford Electrical Engineering department. Professor Boyd introduces a new topic- Model Predictive Control.
Lecture by Professor Stephen Boyd for Convex Optimizations II (EE 364B) in the Stanford Electrical Engineering department. Professor Boyd lectures on Stochastic Model Predictive Control, he then begins discussing Branch-and-bound methods.
Lecture by Professor Stephen Boyd for Convex Optimizations II (EE 364B) in the Stanford Electrical Engineering department. Professor Boyd's final lecture of the quarter is on Branch-and-bound methods.