no code implementations • 27 Nov 2021 • Aaron Yi Ding, Ella Peltonen, Tobias Meuser, Atakan Aral, Christian Becker, Schahram Dustdar, Thomas Hiessl, Dieter Kranzlmuller, Madhusanka Liyanage, Setareh Magshudi, Nitinder Mohan, Joerg Ott, Jan S. Rellermeyer, Stefan Schulte, Henning Schulzrinne, Gurkan Solmaz, Sasu Tarkoma, Blesson Varghese, Lars Wolf
Based on the collective input of Dagstuhl Seminar (21342), this paper presents a comprehensive discussion on AI methods and capabilities in the context of edge computing, referred as Edge AI.
no code implementations • 15 Oct 2021 • Stephanie Holly, Thomas Hiessl, Safoura Rezapour Lakani, Daniel Schall, Clemens Heitzinger, Jana Kemnitz
In this work, we investigated the impact of different hyperparameter optimization approaches in an FL system.
no code implementations • 14 May 2020 • Thomas Hiessl, Daniel Schall, Jana Kemnitz, Stefan Schulte
Federated Learning (FL) is a very promising approach for improving decentralized Machine Learning (ML) models by exchanging knowledge between participating clients without revealing private data.