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ProFed: A Benchmark for Proximity-Based Non-IID Federated Learning Cover

ProFed: A Benchmark for Proximity-Based Non-IID Federated Learning

Journal of Open Research Software
Volume 14 (2026): Issue 1
By: Davide Domini,  Christian Otte Ingemann,  Gianluca Aguzzi,  Lukas Esterle and  Mirko Viroli  
Open Access
|Mar 2026

Authors

Davide Domini

davide.domini@unibo.it

Department of Computer Science and Engineering, University of Bologna, Cesena

Christian Otte Ingemann

otte.christian@outlook.com

Department of Electrical and Computer Engineering, University of Aarhus, Aarhus

Gianluca Aguzzi

gianluca.aguzzi@unibo.it

Department of Computer Science and Engineering, University of Bologna, Cesena

Lukas Esterle

lukas.esterle@ece.au.dk

Department of Electrical and Computer Engineering, University of Aarhus, Aarhus

Mirko Viroli

mirko.viroli@unibo.it

Department of Computer Science and Engineering, University of Bologna, Cesena
DOI: https://doi.org/10.5334/jors.624 | Journal eISSN: 2049-9647
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Language: English
Submitted on: Sep 8, 2025
|
Accepted on: Feb 11, 2026
|
Published on: Mar 2, 2026
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year
Keywords:
Federated Learning,
benchmarks,
performance evaluation,
non-IID data

© 2026 Davide Domini, Christian Otte Ingemann, Gianluca Aguzzi, Lukas Esterle, Mirko Viroli, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.

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