Federated Learning
Federated learning is a machine learning approach in which models are trained across multiple decentralized devices or servers while keeping the underlying data stored locally. This approach improves privacy by avoiding the need to centralize sensitive information. RTI uses federated learning to support secure analytics in health care, social services, and other data-sensitive areas.