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Lecture 3: Newton's Method

Lecture 3: Newton's Method

This video was recorded at MIT 15.084J / 6.252J Nonlinear Programming - Spring 2004. This course introduces students to the fundamentals of nonlinear optimization theory and methods. Topics include unconstrained and constrained optimization, linear and quadratic programming, Lagrange and conic duality theory, interior-point algorithms and theory, Lagrangian relaxation, generalized programming, and semi-definite programming. Algorithmic methods used in the class include steepest descent, Newton's method, conditional gradient and subgradient optimization, interior-point methods and penalty and barrier methods. Course Highlights Nonlinear Programming features videos of three key lectures in their entirety. A set of comprehensive lecture notes are also available, which explains concepts with the help of equations and sample exercises. Course Homepage: 15.084J / 6.252J Nonlinear Programming Spring 2004 Course features at MIT OpenCourseWare page: Syllabus Calendar Readings Lecture Notes Recitations Exams Download Course Materials

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