Convex Optimization II

Video Lectures

Displaying all 18 video lectures.
Lecture 1
Introduction
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Introduction
Lecture by Professor Stephen Boyd for Convex Optimization II (EE 364B) in the Stanford Electrical Engineering department. Professor Boyd's first lecture is on the course requirements, homework assignments, and then goes into his first topic- Subgradients.
Lecture 2
Subgradients
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Subgradients
Lecture by Professor Stephen Boyd for Convex Optimization II (EE 364B) in the Stanford Electrical Engineering department. Professor Boyd continues subgradients.
Lecture 3
Subgradient Methods
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Subgradient Methods
Lecture by Professor Stephen Boyd for Convex Optimization II (EE 364B) in the Stanford Electrical Engineering department. Professor Boyd covers subgradient methods.
Lecture 4
Subgradient Methods for Constrained Problems.
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Subgradient Methods for Constrained Problems.
Lecture by Professor Stephen Boyd for Convex Optimization II (EE 364B) in the Stanford Electrical Engineering department. Professor Boyd lectures on subgradient methods for constrained problems.
Lecture 5
Stochastic Programing and the Localization and Cutting-Plane Methods
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Stochastic Programing and the Localization and Cutting-Plane Methods
Lecture by Professor Stephen Boyd for Convex Optimization II (EE 364B) in the Stanford Electrical Engineering department. Professor Boyd introduces stochastic programing and the localization and cutting-plane methods.
Lecture 6
Analytic Center Cutting-Plane Methods
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Analytic Center Cutting-Plane Methods
Lecture by Professor Stephen Boyd for Convex Optimization 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 7
Ellipsoid Methods
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Ellipsoid Methods
Lecture by Professor Stephen Boyd for Convex Optimization 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 8
Primal and Dual Decomposition Methods
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Primal and Dual Decomposition Methods
Lecture by Professor Stephen Boyd for Convex Optimization II (EE 364B) in the Stanford Electrical Engineering department. Professor Boyd introduces primal and dual decomposition methods.
Lecture 9
Primal and Dual Decomposition Methods (cont.)
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Primal and Dual Decomposition Methods (cont.)
Lecture by Professor Stephen Boyd for Convex Optimization II (EE 364B) in the Stanford Electrical Engineering department. Professor Boyd concludes his lecture on primal and dual decomposition methods.
Lecture 10
Decomposition Applications
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Decomposition Applications
Lecture by Professor Stephen Boyd for Convex Optimization II (EE 364B) in the Stanford Electrical Engineering department. Professor Boyd introduces a new topic, Decomposition Applications.
Lecture 11
Sequential Convex Programming
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Sequential Convex Programming
Lecture by Professor Stephen Boyd for Convex Optimization II (EE 364B) in the Stanford Electrical Engineering department. Professor Boyd lectures on Sequential Convex Programming.
Lecture 12
Conjugate Gradient Methods
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Conjugate Gradient Methods
Lecture by Professor Stephen Boyd for Convex Optimization 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 13
Truncated Newton Method
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Truncated Newton Method
Lecture by Professor Stephen Boyd for Convex Optimization 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 14
L1-Norm Methods for Convex-Cardinality Problems
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L1-Norm Methods for Convex-Cardinality Problems
Lecture by Professor Stephen Boyd for Convex Optimization 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 15
L1 Methods for Convex-Cardinality Problems (cont.)
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L1 Methods for Convex-Cardinality Problems (cont.)
Lecture by Professor Stephen Boyd for Convex Optimization II (EE 364B) in the Stanford Electrical Engineering department. Professor Boyd continues lecturing on L1 Methods for Convex-Cardinality Problems.
Lecture 16
Model Predictive Control
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Model Predictive Control
Lecture by Professor Stephen Boyd for Convex Optimization II (EE 364B) in the Stanford Electrical Engineering department. Professor Boyd introduces a new topic- Model Predictive Control.
Lecture 17
Branch-and-Bound Methods
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Branch-and-Bound Methods
Lecture by Professor Stephen Boyd for Convex Optimization 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 18
Branch-and-Bound Methods (cont.)
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Branch-and-Bound Methods (cont.)
Lecture by Professor Stephen Boyd for Convex Optimization II (EE 364B) in the Stanford Electrical Engineering department. Professor Boyd's final lecture of the quarter is on Branch-and-bound methods.