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D. Schall

4 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author3
  • last author1

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.LG3
  • cs.AI1
same name
  • D. Schall — 5 papers, h 18

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

collaborators

4 papers

cs.LG2021

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…

cs.LG2021

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…

cs.LG2021

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…

cs.AI2020

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…

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