Preprint
Aug 2026
Coordination on a Budget: Federated Active Learning with Few Labels
A new FAL framework is proposed that utilizes federated representation learning to align client data in a shared embedding space that achieves performance that surpasses existing FAL methods even when they are given substantially larger annotation budgets, demonstrating the value of centralized coordination under privacy constraints.
Liam Mohr, D. Weinshall
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