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Age Aware Scheduling for Differentially-Private Federated Learning
This paper explores differentially-private federated learning (FL) across time-varying databases, delving into a nuanced three-way tradeoff involving age, accuracy, and differential privacy (DP).
Iterative Collision Resolution for Slotted ALOHA with NOMA for Heterogeneous Devices
In this paper, the problem of using uncoordinated multiple access (UMA) to serve a massive amount of heterogeneous users is investigated.
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