FSCLB scales federated linear contextual bandits with sketching to achieve over 90% lower computation and communication costs while preserving a near-optimal regret bound of O(sqrt(l d T)).
Federated optimization in heterogeneous networks
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HEW-Local SGD provides exact-weight adaptive aggregation for heterogeneous local SGD with one-step guarantees and explicit convergence results under unequal local horizons.
citing papers explorer
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Scaling Federated Linear Contextual Bandits via Sketching
FSCLB scales federated linear contextual bandits with sketching to achieve over 90% lower computation and communication costs while preserving a near-optimal regret bound of O(sqrt(l d T)).
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Heterogeneous-Horizon Exact-Weight Local SGD
HEW-Local SGD provides exact-weight adaptive aggregation for heterogeneous local SGD with one-step guarantees and explicit convergence results under unequal local horizons.