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An Autoencoder-Based Constellation Design for AirComp in Wireless Federated Learning
In this paper, we propose an end-to-end communication system supporting AirComp with digital modulation, aiming to overcome the challenges associated with accurate decoding of the sum signal with constellation designs.
Communication and Storage Efficient Federated Split Learning
Federated Split Learning (FSL) preserves the parallel model training principle of FL, with a reduced device computation requirement thanks to splitting the ML model between the server and clients.
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