1. A survey on federated learning: The journey from centralized to distributed on-site learning and beyond;AbdulRahman;IEEE Internet Things J.,2020
2. Alsinglawi, B., Alnajjar, F., Mubin, O., Novoa, M., Alorjani, M., Karajeh, O., Darwish, O., 2020. Predicting Length of Stay for Cardiovascular Hospitalizations in the Intensive Care Unit: Machine Learning Approach. In: 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). IEEE. pp. 5442–5445.
3. Antunes, R.S., da Costa, C.A., Küderle, A., Yari, I.A., Eskofier, B. Federated Learning for Healthcare: Systematic Review and Architecture Proposal, ACM Transactions on Intelligent Systems and Technology (TIST).
4. Beutel, D.J., Topal, T., Mathur, A., Qiu, X., Parcollet, T., de Gusmao, P.P.B., Lane, N.D. FLOWER: A friendly federated learning framework, arXiv preprint arXiv:2007.14390.
5. Beutel, D.J., Topal, T., Mathur, A., Qiu, X., Fernandez-Marques, J., Gao, Y., Sani, L., Li, K.H., Parcollet, T., de Gusmão, P.P.B., et al. FLOWER: A friendly federated learning framework.