Publications

High-throughput Simulation of Federated Learning via Resource-Aware Client Placement

Published in arXiv, 2023

This paper is about Pollen, a system that enables high-throughput simulation of federated learning.

Recommended citation: Lorenzo Sani, Pedro Porto Buarque de Gusmão, Alex Iacob, Wanru Zhao, Xinchi Qiu, Yan Gao, Javier Fernandez-Marques, & Nicholas Donald Lane. (2023). High-throughput Simulation of Federated Learning via Resource-Aware Client Placement. https://arxiv.org/abs/2306.17453

Flower: A Friendly Federated Learning Research Framework

Published in arXiv, 2022

This paper is about Flower, the federated learning framework developed at the University of Cambridge by the MLSys group.

Recommended citation: Beutel, D., Topal, T., Mathur, A., Qiu, X., Fernandez-Marques, J., Gao, Y., Sani, L., Kwing, H., Parcollet, T., Gusmão, P., & Lane, N. (2020). Flower: A Friendly Federated Learning Research Framework. arXiv preprint arXiv:2007.14390. https://arxiv.org/abs/2007.14390