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.
Last planned examination: Autumn 2022
Decision to discontinue this course:
No information inserted
Information per course offering
Course offerings are missing for current or upcoming semesters.
Course syllabus as PDF
Please note: all information from the Course syllabus is available on this page in an accessible format.
Course syllabus FSH3217 (Spring 2019–)Headings with content from the Course syllabus FSH3217 (Spring 2019–) are denoted with an asterisk ( )
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.
Recommended prerequisites
Good knowledge of linear algebra and exposure to probability. Exposure to numerical computing, optimization, and application fields helpful but not required; the applications will be kept basic and simple. You will use matlab and CVX to write simple scripts, so some basic familiarity with matlab will be required. Many good matlab tutorials are available online.
Equipment
No information inserted
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
If the course is discontinued, students may request to be examined during the following two academic years.
Grading scale
P, F
Examination
- PRO1 - Project, 4.5 credits, grading scale: P, F
- SEM1 - Seminars, 3.0 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.
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.
Opportunity to complete the requirements via supplementary examination
No information inserted
Opportunity to raise an approved grade via renewed examination
No information inserted
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.
Further information
Course room in Canvas
Registered students find further information about the implementation of the course in the course room in Canvas. A link to the course room can be found under the tab Studies in the Personal menu at the start of the course.
Offered by
Main field of study
This course does not belong to any Main field of study.
Education cycle
Third cycle
Add-on studies
No information inserted
Contact
Mats Danielsson (md@mi.physics.kth.se)