Material Detail
6.079 Introduction to Convex Optimization | Electrical Engineering and Computer Science
This course aims to give students the tools and training to recognize convex optimization problems that arise in scientific and engineering applications, presenting the basic theory, and concentrating on modeling aspects and results that are useful in applications. Topics include convex sets, convex functions, optimization problems, least-squares, linear and quadratic programs, semidefinite programming, optimality conditions, and duality theory. Applications to signal processing, control, machine learning, finance, digital and analog circuit design, computational geometry, statistics, and mechanical engineering are presented. Students complete hands-on exercises using high-level numerical software. Acknowledgements The course materials were developed jointly by Prof. Stephen Boyd (Stanford), who was a visiting professor at MIT when this course was taught, and Prof. Lieven Vanderberghe (UCLA).
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More about this material
- Material Type:
- Online Course
- Date Added to MERLOT:
- May 12, 2016
- Date Modified in MERLOT:
- May 12, 2016
- Author:
- Parrilo, Pablo
- Submitter:
-
Barbra Bied Sperling
- Primary Audience:
- College General Ed, College Lower Division, College Upper Division, Graduate School
- Technical Format:
- Website
- Mobile Compatibility:
- Not specified at this time
- Language:
- English
- Cost Involved:
- No
- Source Code Available:
- No
- Accessibility Information Available:
- Unknown
- Creative Commons:
-
This work is licensed under a Attribution-NonCommercial-ShareAlike 3.0 United States
