Acronym: MultiML
Time: 2022 - 2025
Funder: Federal state
Funder description:

BMBF AI Junior Research Group

Contact person: Sebastian Peitz

The focus of the BMBF funded AI junior research group MultiML is on the development of multiobjective training algorithms for deep learning. Deep neural networks are of utmost importance in many areas of application. However, the consideration of multiple training criteria as well as system knowledge requires further investigation and has great potential for further improvements. In particular, we perform basic research on: The development of efficient optimization algorithms for training neural networks regarding multiple conflicting objective functions; interactive learning and adaptation of deep neural networks using techniques from multiobjective optimization; and consideration of system knowledge, e.g., in the form of conservation laws or differential equations.