Geilo Winter School in eScience
The Geilo Winter Schools are an annual meeting place where young researchers can get updated on new ideas, methods and theories within the eScience field. The schools attract a number of participants to spend a week in Geilo, Norway, in January learning from lectures, collaborating and exchanging ideas and experience. The idea is to cover not only theory, but also how something is done in practice.
The 22nd edition of the Geilo Winter School in eScience will be held in January 2022, and registration is open. You can stay updated on the winter school through this webpage, or on our facebook pages - or add your name to the mailing list by sending an email to email@example.com. Please also take a look at the webpages for the previous schools for more information and a feel for typical school contents.
Topic: Continuous Optimization
Time: January 23-28, 2022
Place: Dr. Holms Hotel, Geilo, Norway
The 22nd edition of the Geilo Winter School will take place in Geilo, Norway, from Sunday January 23 to Friday January 28, 2022. The topic of the school will be continuous optimization.
Continuous optimization is the study of maximizing functions of continuous variables. Such problems are generally intractable without additional conditions and constraints, but for many specific cases, theoretical research has led to the development of very useful algorithms for practical applications. Today, such algorithms constitute the workhorse in a diverse range of applications spanning from robotics over machine learning to economics. Recent successes in the field include progress in compressed sensing and advances in large-scale optimization.
The 2022 Geilo winter school features an exciting weeklong program with introduction to continuous optimization and deep dives into various applications including shape optimization, optimization of physical systems constrained by partial differential equations, and relations between machine learning and optimization. The goal of the school is not only to teach the basics of the field, but also to provide practical understanding of how and when continuous optimization might be applied.