5 citations · 6 across the 5 of their papers we have counts for
6 papers
Evaluation of Hyperparameter-Optimization Approaches in an Industrial Federated Learning System
Stephanie Holly, Thomas Hiessl, Safoura Rezapour Lakani +3
Federated Learning (FL) decouples model training from the need for direct access to the data and allows organizations to collaborate with industry partners to reach a satisfying le…
Minimal-Configuration Anomaly Detection for IIoT Sensors
Clemens Heistracher, Anahid Jalali, Axel Suendermann +4
The increasing deployment of low-cost IoT sensor platforms in industry boosts the demand for anomaly detection solutions that fulfill two key requirements: minimal configuration ef…
Towards Robust and Transferable IIoT Sensor based Anomaly Classification using Artificial Intelligence
Jana Kemnitz, Thomas Bierweiler, Herbert Grieb +2
The increasing deployment of low-cost industrial IoT (IIoT) sensor platforms on industrial assets enables great opportunities for anomaly classification in industrial plants. The p…
Industrial Federated Learning -- Requirements and System Design
Thomas Hiessl, Daniel Schall, Jana Kemnitz +1
Federated Learning (FL) is a very promising approach for improving decentralized Machine Learning (ML) models by exchanging knowledge between participating clients without revealin…
Energy and Performance-Can a Wimpy-Node Cluster Challenge a Brawny Server?
Daniel Schall, Theo Härder
Traditional DBMS servers are usually over-provisioned for most of their daily workloads and, because they do not show good energy proportionality, waste a lot of energy while under…
Dynamic Physiological Partitioning on a Shared-nothing Database Cluster
Daniel Schall, Theo Härder
Traditional DBMS servers are usually over-provisioned for most of their daily workloads and, because they do not show good-enough energy proportionality, waste a lot of energy whil…