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- Author:
-
Stephen Boyd
- Subject:
- Mathematics and Statistics, Science and Technology
- Institution Name:
- Stanford University
- Collection:
-
Stanford University - School of Engineering
- Grade Level:
- Post-secondary
- Abstract:
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.
- Languages:
- English
- Material Type:
- Audio Lectures, Full Course, Lesson Plans, Video Lectures
- Media Format:
- Audio, Text/HTML, Downloadable docs, Video
- Conditions of Use:
-
Creative Commons Attribution 3.0
- Copyright Holder:
- Stanford University
No restrictions on your remixing, redistributing, or making derivative works.
Give credit to the author, as required.
Your remixing, redistributing, or making derivatives works comes with some
restrictions, including how it is shared.
Your redistributing comes with some restrictions. Do not remix or make
derivative works.
Copyrighted materials, available under Fair Use and the TEACH Act for US-based
educators, or other custom arrangements. Go to the resource provider to see
their individual restrictions.
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