A Practical Influence Approximation for Privacy-Preserving Data Filtering in Federated Learning

no code implementations • 23 May 2022 • Ljubomir Rokvic, Panayiotis Danassis, Boi Faltings

Federated Learning by nature is susceptible to low-quality, corrupted, or even malicious data that can severely degrade the quality of the learned model.

Data Valuation Federated Learning +2