Federated learning is a machine learning technique that allows several individuals, dubbed “clients,” to collaboratively train a model, without sharing raw training data with each other. This “shared training” approach could be particularly advantageous for training machine learning models designed to complete tasks in financial and health care settings, without accessing people’s personal data.
Lancelot federated learning system combines encryption and robust aggregation to resist poisoning attacks
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