Automated Algorithm Selection: Using Machine Learning for Efficient Optimization

Datum

24.11.2021

Zeit

13:30 - 15:00

Sprecher

Prof. Pascal Kerschke

Zugehörigkeit

TU Dresden, ScaDS.AI Dresden/Leipzig

Sprache

en

Hauptthema

Informatik

Host

ScaDS.AI Dresden/Leipzig

Beschreibung

Optimization is an integral part of our lives: engineers fine-tune the shape of mechanical components, businesses aim at minimizing their costs, space agencies like NASA wait for the best possible conditions to launch their space shuttles, and in our private lives we use navigation systems to find the fastest route between two places. Many of these problems can be formulated as an optimization problem, which can then be "solved" using a suitable optimization algorithm. However, usually there is no algorithm that is superior to all its competitors. Consequently, even the choice of the "right" algorithm (for the optimization of a given problem instance) is a challenging task, and the choice of the "wrong" optimization algorithm can severely affect the overall performance. In my presentation, I will introduce the general idea of automated algorithm selection and thereby demonstrate how machine learning can be used to efficiently solve such tasks. Subsequently, I will outline the current state of research for an exemplary optimization task and finally discuss the respective benefits, open challenges, and research perspectives.

Links

• Program and registration

Letztmalig verändert: 22.11.2021, 19:02:32