MA8022 - Convex Optimization | ||||||||
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| * The offering term is subject to change without prior notice | ||||||||
Course Aims | ||||||||
This course aims to introduce students to the field of modern convex optimization, which generalizes least-squares, linear and quadratic programming, and semidefinite programming, and forms the basis of many methods for non-convex optimization. Students will learn to recognize and solve convex optimization problems that arise in applications, gain insight in algorithm analysis and design, and obtain a solid understanding of the theoretical foundations of the subject. | ||||||||
Assessment (Indicative only, please check the detailed course information) | ||||||||
Continuous Assessment: 50% | ||||||||
Examination: 50% | ||||||||
Examination Duration: 3 hours | ||||||||
Detailed Course Information | ||||||||
| MA8022.pdf | ||||||||
Useful Links | ||||||||
| Department of Mathematics | ||||||||
