Learning on non - Euclidean data


In the framework of the OEAD program "Scientific and Technical Cooperation" (STC)  the project  "Collective evolution strategies for distributed learning on non-Euclidean data" to establish joint research activities between the research centre Business Informatics of the Vorarlberg University of Applied Sciences and the Department of Mathematics of the University of Montenegro.

Over the two-year duration, the project teams will work out common research questions in several bilateral workshops. The focus will be on the topics

  • Evolutionary Algorithms

  • Self-organizing complex physical systems

To combine these topics, in particular problems involving  non-Euclidean geometry shall be considered. Applications of such problems can be found for example

  • in simultaneous communication between actors

  • in shape optimization for the purpose of image recognition/computer graphics
  • in the design of neural networks for dynamic problems

In addition to developing new methods, the collaboration will be used to prepare other joint research projects.



project name Collective evolution strategies for distributed learning on non-Euclidean data
Program Austrian Exchange Service (OEAD)
Topic Basic research
Project Index Number ME 06/2020
Project Duration January 2021 - December 2022
Project Budget 7,200.00 EUR


Dr.rer.nat. Michael HELLWIG
Head Josef Ressel Center for Robust Decisions, Senior Researcher
Prof.(FH) Dipl.-Ing. Dr. rer. nat. habil Hans-Georg BEYER
Research professor: Computational Intelligence especially Evolutionary Algorithms