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Federated Learning

Ορισμός

A machine learning approach where models are trained across multiple decentralised devices or servers holding local data, without that data ever leaving its origin. Federated learning is valuable for healthcare, finance, and any sector where GDPR data minimisation principles make centralised training impractical.

Σχετικοί Όροι

Data Minimisation

The GDPR principle requiring that only the minimum necessary personal data be collected and processed for a specified purpose. Applied to AI, data minimisation drives techniques like federated learning, synthetic data generation, and differential privacy to train effective models without retaining raw personal data.

Machine Learning (ML)

A subset of AI that enables systems to automatically learn and improve from experience without being explicitly programmed. ML algorithms build models based on training data to make predictions or decisions.