Lecturer : Prof. Stephen Boyd
University of : Stanford ( USA )
Year : 2010
Level : Undergraduate
University of : Stanford ( USA )
Year : 2010
Level : Undergraduate
Course Description :
This course is an introduction to 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.
List of Lectures :
Lecture 1: Introduction
Lecture 2: Guest Lecturer: Jacob Mattingley
Lecture 3: Logistics, Convex Functions
Lecture 4: Vector Composition
Lecture 5: Optimal And Locally Optimal Points
Lecture 6: Linear-Fractional Program
Lecture 7: Generalized Inequality Constraints
Lecture 8: Lagrangian, Lagrange Dual Function
Lecture 9: Complementary Slackness
Lecture 10: Applications Section Of The Course
Lecture 11: Statistical Estimation
Lecture 12: Continue On Experiment Design
Lecture 13: Linear Discrimination (Cont.),
Lecture 14: LU Factorization (Cont.)
Lecture 15: Algorithm Section Of The Course
Lecture 16: Continue On Unconstrained Minimization
Lecture 17: Newton
Lecture 18: Logarithmic Barrier
Lecture 19: Interior-Point Methods
Lecture 1: Introduction
Lecture 2: Guest Lecturer: Jacob Mattingley
Lecture 3: Logistics, Convex Functions
Lecture 4: Vector Composition
Lecture 5: Optimal And Locally Optimal Points
Lecture 6: Linear-Fractional Program
Lecture 7: Generalized Inequality Constraints
Lecture 8: Lagrangian, Lagrange Dual Function
Lecture 9: Complementary Slackness
Lecture 10: Applications Section Of The Course
Lecture 11: Statistical Estimation
Lecture 12: Continue On Experiment Design
Lecture 13: Linear Discrimination (Cont.),
Lecture 14: LU Factorization (Cont.)
Lecture 15: Algorithm Section Of The Course
Lecture 16: Continue On Unconstrained Minimization
Lecture 17: Newton
Lecture 18: Logarithmic Barrier
Lecture 19: Interior-Point Methods
: لينك خريد
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