IEEE P3652.1 - IEEE Draft Guide for Architectural Framework and Application of Federated Machine Learning
Project Details
federated machine learning defines a machine learning framework that allows a collective model to be constructed from data that is distributed across repositories owned by different organizations or devices. This guide provides a blueprint for data usage and model building across organizations and devices while meeting applicable privacy, security and regulatory requirements. It defines the architectural framework and application guidelines for federated machine learning, including 1) description and definition of federated machine learning, 2) the categorizes federated machine learning and the application scenarios to which each category applies, 3) performance evaluation of federated machine learning and 4) associated regulatory requirements.
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