Author

Andrea Luna

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Preprint Jul 2026

FedAvg for HAR: Exploring the Tradeoff Between Personalized and Generalization Accuracy

Experimental results of the FedAvg algorithm applied to the Human Activity Recognition domain show that, although FedAvg confirms a higher degree of personalization capabilities while keeping a high degree of generalization with respect to the traditional centralized learning, this result is not so obvious under stressful conditions, such as when varying class distribution over clients.

Andrea Luna, Susanna Peretti, C. Contoli et al. · 0 citations