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Bayesian Federated Learning over Wireless Networks
This paper proposes a Bayesian federated learning (BFL) algorithm to aggregate the heterogeneous quantized gradient information optimally in the sense of minimizing the mean-squared error (MSE).
Active Learning with Multiple Kernels
In this paper, we introduce a new research problem, termed (stream-based) active multiple kernel learning (AMKL), in which a learner is allowed to label selected data from an oracle according to a selection criterion.
Supervised-Learning for Multi-Hop MU-MIMO Communications with One-Bit Transceivers
The idea is to update the model parameters with a reliably detected data symbol by treating it as a new training (labelled) data.
Information Theory Information Theory
