FedSteer constructs a gradient subspace from cached client updates, projects active gradients to obtain coordinates, and reuses those coordinates on the drifted subspace to correct extreme staleness in federated learning.
arXiv preprint arXiv:2409.17446 , year=
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FedSteer: Taming Extreme Gradient Staleness in Federated Learning with Corrective Projections and Caching
FedSteer constructs a gradient subspace from cached client updates, projects active gradients to obtain coordinates, and reuses those coordinates on the drifted subspace to correct extreme staleness in federated learning.