EMERGE 2024

Enabling Machine Learning Operations for next-Gen Embedded Wireless Networked Devices
December 10, 2024

Accepted Papers


Efficient and Effective Multi-Objective AutoML for Industrial Data Analytics
Tanmay Goyal (ABB Research & Development Center, DE), Pengcheng Huang, Balz Maag (ABB Research Center, CH)

FLAME: Adaptive and Reactive Concept Drift Mitigation for Federated Learning Deployments
Ioannis Mavromatis (Digital Catapult, UK), Stefano De Feo (University of Bristol, UK), Aftab Khan (Toshiba Europe Ltd. Bristol, UK)

MatchCurv: Communication-Efficient Decentralized Federated Learning in Heterogeneous Environments
Harsha Praneeth Dussa, Janek Haberer, Olaf Landsiedel (Kiel University, DE)

Customizing Pre-Processing Algorithms for Streaming Sensor Data on Embedded Networked Devices
Dragos Lazea, Tudor Cioara, Anca Hangan (Technical University of Cluj-Napoca, RO), Zsolt Istvan (Technical University of Darmstadt, DE)

Breaking the Illusion: Real-world Challenges for Adversarial Patches in Object Detection
Jakob Schack, Katarina Petrovic (Graz University of Technology, AU), Olga Saukh (Institute of Technical Informatics, Graz University of Technology, AU)

EVs Coordination to Maximize the Usage of Local Renewable Energy
Cristina Pop, Viorica Chifu, Anamaria Raita, Tudor Cioara, Ionut Anghel, Marius Joldos (Technical University of Cluj-Napoca, RO)