Grundläggande teori för konvex optimering och praktisk träning hur man löser problem relaterade till konvex optimering så att man kan tillämpa på problem inom den egna forskningen.
FSH3217 Convex Optimization within Medical Imaging 7.5 credits
This course has been discontinued.
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Course syllabus as PDF
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Course syllabus FSH3217 (Spring 2019–)Content and learning outcomes
Course contents
Intended learning outcomes
After completing the course, the PhD students should:
- have tools and training to recognize convex optimization problems that rise in applications
- be able to present the basic theory of such problems, concentrating on results that are useful in computation
- have a thorough understanding of how such problems are solved, and some experience in solving them
- have the background required to use the methods in their own research work or applications.
Literature and preparations
Specific prerequisites
Enrolled as PhD student.
Literature
Convex Optimization by Stephen Boyd and Lieven Vandenberghe, Cambridge University Press
Video lectures:
https://class.stanford.edu/courses/Engineering/CVX101/Winter2014/f0e5ca452f9a437c83af75626d196df0/
Examination and completion
Grading scale
Examination
- SEM1 - Seminars, 3.0 credits, grading scale: P, F
- PRO1 - Project, 4.5 credits, grading scale: P, F
Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability.
The examiner may apply another examination format when re-examining individual students.
If the course is discontinued, students may request to be examined during the following two academic years.
Oral and written presentation of the solution of a relevant optimization problem related to your own research, 7,5 hp, Grading: P/F
Other requirements for final grade
Approval of oral and written presentation of problem assignment.
Examiner
Ethical approach
- All members of a group are responsible for the group's work.
- In any assessment, every student shall honestly disclose any help received and sources used.
- In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.