Please note! Course description is confirmed for two academic years (1.8.2018-31.7.2020), which means that in general, e.g. Learning outcomes, assessment methods and key content stays unchanged. However, via course syllabus, it is possible to specify or change the course execution in each realization of the course, such as how the contact sessions are organized, assessment methods weighted or materials used.
Students will be introduced and traines for some fundamental skills for solving convex optimization problems. They will be introduced to duality theory and optimality conditions. They will build a background required to use the convex optimization methods and numerical algorithms in their own research or engineering work. They will be also provided with a number of examples of successful application of convex optimization techniques in engineering, science, and economics.
Schedule: 28.10.2020 - 09.12.2020
Teacher in charge (valid 01.08.2020-31.07.2022): Jorma Skyttä, Sergiy Vorobyov
Teacher in charge (applies in this implementation): Jorma Skyttä, Sergiy Vorobyov
Contact information for the course (applies in this implementation):
CEFR level (applies in this implementation):
Language of instruction and studies (valid 01.08.2020-31.07.2022):
Teaching language: English
Languages of study attainment: English
CONTENT, ASSESSMENT AND WORKLOAD
Optimality conditions, duality theory, theorems of alternative. Minimax, extremal volume, and other application problems. Introduction to interior-point methods.
Assessment Methods and Criteria
Lectures, exercises, assignments, final exam.
Lectures, exercises, final exam approximately 30 h
Assignments, independent work approximately 103 h
Total 133 h
Attendance in some contact teaching may be compulsory.
Recommended ELEC-E5422 Convex Optimization I P and a course on Linear Algebra or Matrix Computations
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