pFedSOP combines Gompertz-weighted local/global gradients with a rank-one Fisher Information Matrix update to speed up personalized federated learning, but the convergence proof is invalid and the update reduces to normalized gradient descent.
Towards personalized federated learning,
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pFedSOP : Accelerating Training Of Personalized Federated Learning Using Second-Order Optimization
pFedSOP combines Gompertz-weighted local/global gradients with a rank-one Fisher Information Matrix update to speed up personalized federated learning, but the convergence proof is invalid and the update reduces to normalized gradient descent.