Abstract: Meta-learning aims to leverage prior knowledge from related tasks to enable a base learner to quickly adapt to new tasks with limited labeled samples. However, traditional meta-learning ...
Abstract: This paper proposes a variational Bayesian learning framework for the end-to-end design of frequency-division duplex (FDD) massive Multiple Input Multiple Output (MIMO) communication systems ...
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