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Found 4 papers, 1 papers with code
Over-the-Air Split Learning with MIMO-Based Neural Network and Constellation-Based Activation
The precoding and combining matrices are trainable parameters in such a system, whereas the MIMO channel is implicit.
Over-the-Air Split Machine Learning in Wireless MIMO Networks
In such a split ML system, the precoding and combining matrices are regarded as trainable parameters, while MIMO channel matrix is regarded as unknown (implicit) parameters.
Sufficient-Statistic Memory AMP
Given an arbitrary MAMP, we can construct an SS-MAMP by damping, which not only ensures the convergence of the state evolution, but also preserves the orthogonality, i. e., its dynamics can be correctly described by state evolution.
Communication-Efficient Federated Learning with Binary Neural Networks
{ Numerical results show that the proposed FL framework significantly reduces the communication cost compared to the conventional neural networks with typical real-valued parameters, and the performance loss incurred by the binarization can be further compensated by a hybrid method.
