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Communication Trade-offs in Federated Learning of Spiking Neural Networks
We investigate federated learning for training multiple SNNs at clients when two mechanisms reduce the uplink communication cost: i) random masking of the model updates sent from the clients to the server; and ii) client dropouts where some clients do not send their updates to the server.
Random Features Model with General Convex Regularization: A Fine Grained Analysis with Precise Asymptotic Learning Curves
We compute precise asymptotic expressions for the learning curves of least squares random feature (RF) models with either a separable strongly convex regularization or the $\ell_1$ regularization.
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