Feature-Based Dataset Fingerprinting for Clustered Federated Learning on Medical Image Data

Federated Learning (FL) allows multiple clients to train a common model without sharing their private training data. In practice, federated optimization struggles with sub-optimal model utility because data is not independent and identically distributed (non-IID). Recent work has proposed to cluster...

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Bibliographic Details
Main Authors: Daniel Scheliga, Patrick Mäder, Marco Seeland
Format: Article
Language:English
Published: Taylor & Francis Group 2024-12-01
Series:Applied Artificial Intelligence
Online Access:https://www.tandfonline.com/doi/10.1080/08839514.2024.2394756
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