AutoFLIP prunes federated models via one-time collective loss-landscape mapping and client-agreement-guided adaptation, reporting 52% lower computation and 65% lower communication with SOTA non-IID accuracy.
A vision of 6g wireless systems: Applications, trends, technologies, and open research problems
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Pruning Federated Models through Loss Landscape Analysis and Client Agreement Scoring
AutoFLIP prunes federated models via one-time collective loss-landscape mapping and client-agreement-guided adaptation, reporting 52% lower computation and 65% lower communication with SOTA non-IID accuracy.