The Federated Learning Community Group has been launched:
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.
This is a community initiative. This group was originally proposed on 2021-11-04 by Wonsuk Lee. The following people supported its creation: Wonsuk Lee, Sungpil Shin, Daniel Hark SOHN, Hyojin Song, Seungyun Lee, Sungyoung Son, Jiwoong YOO, Ryuan Choi, JIN BYUNG LEE, Wooglae Kim, Changjin Jeong, Hyungwook Lee, Geunhyung Kim, Pablo COCA, Kangchan Lee, Patrick Guerrero. W3C’s hosting of this group does not imply endorsement of the activities.
We invite you to share news of this new group in social media and other channels.
If you believe that there is an issue with this group that requires the attention of the W3C staff, please email us at email@example.com
W3C Community Development Team