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IEEE 3652.1-2020

IEEE Guide for Architectural Framework and Application of Federated Machine Learning

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. A blueprint for data usage and model building across organizations and devices while meeting applicable privacy, security and regulatory requirements is provided in this guide. It defines the architectural framework and application guidelines for federated machine learning, including description and definition of federated machine learning; the categories federated machine learning and the application scenarios to which each category applies; performance evaluation of federated machine learning; and associated regulatory requirements.

Sponsor Committee
C/AISC - Artificial Intelligence Standards Committee
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PAR Approval
Board Approval

Working Group Details

IEEE Computer Society
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Sponsor Committee
C/AISC - Artificial Intelligence Standards Committee
Working Group
FML - Federated Machine Learning
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IEEE Program Manager
Christy Bahn
Working Group Chair
Qiang Yang
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