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 - Sponsor Committee
- C/AISC - Artificial Intelligence Standards Committee
- Working Group
-
FML - Federated Machine Learning
Learn More - IEEE Program Manager
- Christy Bahn
Contact - Working Group Chair
- Qiang Yang
No Active Projects
No Active Standards
No Superseded Standards
No Inactive-Withdrawn Standards
No Inactive-Reserved Standards