AI Termcirca 2016· Added Aug 14, 2026
Federated Learning
A machine learning approach that enables multiple actors to collaborate on model training while maintaining data privacy.
Federated learning is a decentralized machine learning approach that allows multiple actors, such as organizations or individuals, to collaborate on model training while maintaining the privacy and security of their data. This approach enables the development of more accurate and robust models, as it leverages the collective knowledge and data of multiple parties, without requiring them to share their sensitive information. Federated learning has numerous applications in areas like healthcare, finance, and autonomous vehicles, where data privacy and security are paramount.
Examples
- Google's Federated Learning framework
- Apple's Differential Privacy-based Federated Learning
Common misconceptions
- Federated learning requires a centralized authority
- Federated learning is only applicable to deep learning models
Also known as: collaborative machine learning, decentralized machine learning
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