TraceFL: Interpretability-Driven Debugging in Federated Learning via Neuron Provenance

In Federated Learning, clients train models on local data and send updates to a central server, which aggregates them into a global model using a fusion algorithm. This collaborative yet privacy-preserving training comes at a cost. FL developers face significant challenges in attributing global mode...

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Veröffentlicht in:	Proceedings / International Conference on Software Engineering S. 2264 - 2276
Hauptverfasser:	Gill, Waris, Anwar, Ali, Gulzar, Muhammad Ali
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 26.04.2025
Schlagworte:	Accuracy Data models Debugging Explainability Federated learning Interpretability Location awareness Machine Learning Neurons Predictive models Text categorization Training Transformer Transformers
ISSN:	1558-1225
Online-Zugang:	Volltext
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