1. McMahan, H.B., Moore, E., Ramage, D., Hampson, S., Arcas, B.A.: Communication-efficient learning of deep networks from decentralized data. In 20th International Conference on Artificial Intelligence and Statistics, vol. 54, pp. 1273–1282. PMLR (2017)
2. TensorFlow Federated: Machine Learning on Decentralized Data. https://www.tensorflow.org/federated. Accessed 01 Sept 2023
3. Federated Learning from Research to Practice. https://www.pdl.cmu.edu/SDI/2019/slides/2019-09-05Federated%20Learning.pdf. Accessed 01 Sept 2023
4. Kholod, I., et al.: Open-source federated learning frameworks for IoT: a comparative review and analysis. Sensors 21(167), 1–22 (2021). https://doi.org/10.3390/s21010167
5. Popovic, M., Popovic, M., Kastelan, I., Djukic, M., Ghilezan, S.: A simple Python testbed for federated learning algorithms. In: 2023 Zooming Innovation in Consumer Technologies Conference, Piscataway, New Jersey, USA, pp. 148–153. IEEE Xplore (2023). https://doi.org/10.1109/ZINC58345.2023.10173859