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
- Status
- Active Standard
- PAR Approval
- 2018-12-05
- Board Approval
- 2020-09-24
- History
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- Published:
- 2021-03-19
Working Group Details
- Society
- IEEE Computer Society
Learn More About IEEE Computer Society - Sponsor Committee
- C/AISC - Artificial Intelligence Standards Committee
- Working Group
-
FML - Federated Machine Learning
- IEEE Program Manager
- Christy Bahn
Contact Christy Bahn - Working Group Chair
- Qiang Yang
Other Activities From This Working Group
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