227-0690-11L  Large-Scale Convex Optimization

SemesterSpring Semester 2021
LecturersG. Banjac
Periodicityyearly recurring course
Language of instructionEnglish


227-0690-11 VLarge-Scale Convex Optimization2 hrs
Tue16-18HG F 1 »
G. Banjac
227-0690-11 ULarge-Scale Convex Optimization2 hrs
Fri10-12CAB G 61 »
G. Banjac

Catalogue data

AbstractConvex 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.
ObjectiveStudents should be able to apply the fundamental results in convex analysis and numerical methods to analyze and solve large-scale convex optimization problems.
ContentConvex 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.
Lecture notesAvailable on the course Moodle platform.
Prerequisites / NoticeSufficient mathematical maturity, in particular in linear algebra and analysis.

Performance assessment

Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
ECTS credits4 credits
ExaminersG. Banjac
Typegraded semester performance
Language of examinationEnglish
RepetitionRepetition only possible after re-enrolling for the course unit.

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