18 episodes
Convex Optimization (EE364B) Stephen Boyd
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- Technology
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.
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1. Convex Optimization II Lecture 1
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.
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2. Convex Optimization II Lecture 2
Lecture by Professor Stephen Boyd for Convex Optimizations II (EE 364B) in the Stanford Electrical Engineering department. Professor Boyd continues subgradients.
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3. Convex Optimization II Lecture 3
Lecture by Professor Stephen Boyd for Convex Optimizations II (EE 364B) in the Stanford Electrical Engineering department. Professor Boyd covers subgradient methods.
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4. Convex Optimization II Lecture 4
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.
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5. Convex Optimization II Lecture 5
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.
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6. Convex Optimization II Lecture 6
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.