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FedPIDAvg: A PID Controller Inspired Aggregation Method for Federated Learning.
In:. Berlin [u.a.]: Springer, 2023. 209-217 (Lect. Notes Comput. Sc. ; 14092 LNCS)
This paper presents FedPIDAvg, the winning submission to the Federated Tumor Segmentation Challenge 2022 (FETS22). Inspired by FedCostWAvg, our winning contribution to FETS21, we contribute an improved aggregation strategy for federated and collaborative learning. FedCostWAvg is a weighted averaging method that not only considers the number of training samples of each cluster but also the size of the drop of the respective cost function in the last federated round. This can be interpreted as the derivative part of a PID controller (proportional-integral-derivative controller). In FedPIDAvg, we further add the missing integral term. Another key challenge was the vastly varying size of data samples per center. We addressed this by modeling the data center sizes as following a Poisson distribution and choosing the training iterations per center accordingly. Our method outperformed all other submissions.
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Publikationstyp
Artikel: Konferenzbeitrag
Schlagwörter
Brain Tumor Segmentation ; Control ; Federated Learning ; Machine Learning ; Miccai Challenges ; Mri ; Multi-modal Medical Imaging
ISSN (print) / ISBN
0302-9743
e-ISSN
1611-3349
Zeitschrift
Lecture Notes in Computer Science
Quellenangaben
Band: 14092 LNCS,
Seiten: 209-217
Verlag
Springer
Verlagsort
Berlin [u.a.]
Nichtpatentliteratur
Publikationen
Institut(e)
Institute for Tissue Engineering and Regenerative Medicine (ITERM)
Förderungen
Graduate School of Bioengineering, Technical University of Munich
International Graduate School of Science and Engineering (IGSSE)
Technical University of Munich -Institute for Advanced Study - German Excellence Initiative
Translational Brain Imaging Training Network (TRABIT) under the European Union's 'Horizon 2020' research & innovation program
DCoMEX project - Federal Ministry of Education and Research of Germany
'Ecole normale superieure in Paris
International Graduate School of Science and Engineering (IGSSE)
Technical University of Munich -Institute for Advanced Study - German Excellence Initiative
Translational Brain Imaging Training Network (TRABIT) under the European Union's 'Horizon 2020' research & innovation program
DCoMEX project - Federal Ministry of Education and Research of Germany
'Ecole normale superieure in Paris