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Large-Scale Convex Optimization
Last Updated: 2026-06-03 00:14:06
Abstract
Convex optimization has revolutionized modern decision making and underpins many scientific and engineering disciplines. To enable its use in modern large-scale applications, we require new analytical methods that address limitations of existing solutions. This course is intended to provide a comprehensive overview of convex analysis and numerical methods for large-scale optimization.
Objective
Students should be able to apply the fundamental results in convex analysis and numerical methods to analyze and solve large-scale convex optimization problems.
Content
Convex analysis and methods for large-scale optimization. Topics will include: convex sets and functions ; duality theory ; optimality and infeasibility conditions ; structured optimization problems ; gradient-based methods ; operator splitting methods ; distributed and decentralized optimization ; applications in various research areas.
Resources
Lecture Notes
Available on the course Moodle platform.
General Information
- Language
- English
- Levels
- DR , MSC
- Frequency
- Yearly recurring
Examination
- Type
- graded semester performance
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| lecture |
Large-Scale Convex Optimization
This course will be offered as a block course between 01.06.2026 - 12.06.2026.
|
|
2 h weekly |
| exercise |
Large-Scale Convex Optimization
This course will be offered as a block course between 01.06.2026 - 12.06.2026.
|
|
1 h weekly |
Offered In
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Biomedical Engineering Master (Only courses offered under "GESS Science in Perspective" count in this category. See "Offered in" tab in course view. For more information, please refer to )
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Recommended Elective Courses (These courses are particularly recommended for the Bioelectronics track. Please consult your track adviser if you wish to select other subjects.)
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Electives (In the ‘electives’ subcategory, at least two course units must be successfully completed. All courses listed as core courses (not electives) for one of the following ETH MSc programmes, MSc Statistics, MSc Physics, MSc Computer Science, MSc (Applied) Mathematics, MSc Neural Systems and Computation, MSc Robotics, Systems, and Control, MSc Data Science, MSc Electrical Engineering and Information Technology, can be taken as an elective course in the MSc CSE without prior permission.)
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Track: Computers and Networks (The core courses and specialization courses below are a selection for students who wish to specialize in the area of "Computers and Networks", see . The individual study plan is subject to the tutor's approval.)
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Specialization Courses (These specialization courses are particularly recommended for the area of "Computers and Networks", but you are free to choose courses from any other field in agreement with your tutor. Semester / Research Projects are not allowed in this category. A minimum of 40 credits must be obtained from specialization courses during the Master's Programme.)
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Track: Systems and Control (The core courses and specialization courses below are a selection for students who wish to specialize in the area of "Systems and Control", see . The individual study plan is subject to the tutor's approval.)
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Core Courses (These core courses are particularly recommended for the field of "Systems and Control". You may choose core courses form other fields in agreement with your tutor. A minimum of 24 credits must be obtained from core courses during the MSc EEIT.)
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Specialization Courses (These specialization courses are particularly recommended for the area of "Systems and Control", but you are free to choose courses from any other field in agreement with your tutor. Semester / Research Projects are not allowed in this category. A minimum of 40 credits must be obtained from specialization courses during the Master's Programme.)
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Doctorate Information Technology and Electrical Engineering (A minimum of 12 ECTS credit points must be obtained during doctoral studies (also see sub-categories for details) More Information at )
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Subject Specialisation (The courses on offer below are but a small selection out of a much larger available number of courses. Please discuss your course selection with your PhD supervisor.)
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