Federated Learning Community Group
The purpose of this community group is to establish and explore the necessary standards related with the Web for federated learning via the analysis of current implementations related with federated learning such as TensorFlow Federated. The main idea of federated learning is to build machine learning models based on data sets that are distributed across multiple clients (e.g. mobile devices or whole organizations) while preventing data leakage. Therefore, federated learning can give benefits like mitigation of privacy risks and costs.
- Homepage
- Homepage/Blog
- Shortname
- federated-learning
Participation
To join or leave this group, please sign in to your account.
Leadership
- Chairs
-
- Wonsuk Lee
- Sungpil Shin
Links
- Mailing List
- public-federated-learning
