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Found 2 papers, 1 papers with code
Joint User Pairing and Beamforming Design of Multi-STAR-RISs-Aided NOMA in the Indoor Environment via Multi-Agent Reinforcement Learning
Motivated by the above, we study the joint user pairing for NOMA and beamforming design of Multi-STAR-RISs in an indoor environment.
Federated Learning with Intermediate Representation Regularization
Specifically, FedIntR computes a regularization term that encourages the closeness between the intermediate layer representations of the local and global models.
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