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20222026
most citedFedDRL: Deep Reinforcement Learning-based Adaptive Aggregation for Non-IID Data in Federated Learning

2 citations · 2 across the 4 of their papers we have counts for

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cs.LG2026

Diffusion-Inspired Reconfiguration of Transformers for Uncertainty Calibration

Manh Cuong Dao, Quang Hung Pham, Phi Le Nguyen +3

Uncertainty calibration in pre-trained transformers is critical for their reliable deployment in risk-sensitive applications. Yet, most existing pre-trained transformers do not hav…

cs.LG2022★ 2 cited

FedDRL: Deep Reinforcement Learning-based Adaptive Aggregation for Non-IID Data in Federated Learning

Nang Hung Nguyen, Phi Le Nguyen, Duc Long Nguyen +4

The uneven distribution of local data across different edge devices (clients) results in slow model training and accuracy reduction in federated learning. Naive federated learning…