FedFIBoS: Fisher importance based optimal submodelling for heterogeneous federated learning
Read the original at arxiv.org→arXiv:2609.19559v1 Announce Type: new Abstract: Heterogeneous federated learning requires clients with diverse computational capacities to collaboratively train a global model, where each client trains a...
Original headline: "FedFIbOS: Fisher Importance based Optimal Submodelling for Heterogeneous Federated Learning"
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- Sep 18, 04:00 UTC arXiv cs.LG lead source FedFIbOS: Fisher Importance based Optimal Submodelling for Heterogeneous Federated Learning