AUG 10, 2026 · PREPRINT
FedTVD: Balancing Data Quality and Quantity for Robust Federated Learning
arXiv
This is an algorithm development paper presenting a computational method without clinical or real-world validation; it demonstrates improved performance on image classification benchmarks but does not address whether the approach solves a genuine problem in federated learning deployment or generalize beyond simulation.
Reported
Performance improvement over FedA…up to 10.6%