Alexander Erben

According to our database, Alexander Erben authored at least 7 papers between 2022 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

How Can We Train Deep Learning Models Across Clouds and Continents? An Experimental Study.

Alexander Erben, Ruben Mayer, Hans-Arno Jacobsen

Proc. VLDB Endow., February, 2024

Federated Learning Priorities Under the European Union Artificial Intelligence Act.

Herbert Woisetschläger, Alexander Erben, Bill Marino, Shiqiang Wang, Nicholas D. Lane, Ruben Mayer, Hans-Arno Jacobsen

CoRR, 2024

A Survey on Efficient Federated Learning Methods for Foundation Model Training.

Herbert Woisetschläger, Alexander Erben, Shiqiang Wang, Ruben Mayer, Hans-Arno Jacobsen

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

Federated Fine-Tuning of LLMs on the Very Edge: The Good, the Bad, the Ugly.

Herbert Woisetschläger, Alexander Erben, Shiqiang Wang, Ruben Mayer, Hans-Arno Jacobsen

Proceedings of the Eighth Workshop on Data Management for End-to-End Machine Learning, 2024

2023

FLEdge: Benchmarking Federated Machine Learning Applications in Edge Computing Systems.

Herbert Woisetschläger, Alexander Isenko, Ruben Mayer, Hans-Arno Jacobsen

CoRR, 2023

On Serving Image Classification Models.

Aurora González-Vidal, Alexander Isenko, K. R. Jayaram

Proceedings of the 9th International Workshop on Serverless Computing, 2023

2022

Where Is My Training Bottleneck? Hidden Trade-Offs in Deep Learning Preprocessing Pipelines.

Alexander Isenko, Ruben Mayer, Jeffrey Jedele, Hans-Arno Jacobsen

Proceedings of the SIGMOD '22: International Conference on Management of Data, Philadelphia, PA, USA, June 12, 2022