This guide provides data contribution measurement methods for federated machine learning. The document provides guidance with respect to data trading feasibility for federated machine learning. The guide describes three main aspects: 1) Framework for data contribution evaluation of federated machine learning, 2) specific scenario under data contribution, 3) measurement methods for data contribution of federated machine learning.
- Sponsor Committee
- C/AISC - Artificial Intelligence Standards Committee
- Status
- Active PAR
- PAR Approval
- 2022-12-03
Working Group Details
- Society
- IEEE Computer Society
Learn More About IEEE Computer Society - Sponsor Committee
- C/AISC - Artificial Intelligence Standards Committee
- Working Group
-
DCE-FML - Data Contribution Evaluation in Federated Machine Learning
- IEEE Program Manager
- Christy Bahn
Contact Christy Bahn - Working Group Chair
- Chen Jianing
Other Activities From This Working Group
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