1 code implementation • 28 Jul 2023 • Mahdi Morafah, Weijia Wang, Bill Lin
Many of the works use inconsistent experimental settings and there are no comprehensive studies on the effect of FL-specific experimental variables on the results and practical insights for a more comparable and consistent FL experimental setup.
1 code implementation • 30 Sep 2022 • Mahdi Morafah, Saeed Vahidian, Chen Chen, Mubarak Shah, Bill Lin
Though successful, federated learning presents new challenges for machine learning, especially when the issue of data heterogeneity, also known as Non-IID data, arises.
1 code implementation • 21 Sep 2022 • Saeed Vahidian, Mahdi Morafah, Weijia Wang, Vyacheslav Kungurtsev, Chen Chen, Mubarak Shah, Bill Lin
This small set of principal vectors is provided to the server so that the server can directly identify distribution similarities among the clients to form clusters.
1 code implementation • 20 Aug 2022 • Mahdi Morafah, Saeed Vahidian, Weijia Wang, Bill Lin
Classical federated learning approaches yield significant performance degradation in the presence of Non-IID data distributions of participants.
1 code implementation • 2 May 2021 • Saeed Vahidian, Mahdi Morafah, Bill Lin
The traditional approach in FL tries to learn a single global model collaboratively with the help of many clients under the orchestration of a central server.