AFCL solves federated continual learning without gradients by aggregating local Gram matrices and label statistics, proving exact spatio-temporal invariance: the global model equals centralized joint learning for any data partition.
Heterogeneity-guided client sampling: Towards fast and efficient non-iid federated learning
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AFCL: Analytic Federated Continual Learning for Spatio-Temporal Invariance of Non-IID Data
AFCL solves federated continual learning without gradients by aggregating local Gram matrices and label statistics, proving exact spatio-temporal invariance: the global model equals centralized joint learning for any data partition.