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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
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
Published:
On the 6th of March 2023, Scott Zhao invited the CaMLSys group to run a tutorial about the Flower framework.
Mixed course, University of Cambridge, Department of Computer Science and Technology, 2023
I run in coordination with Alexandru-Andrei Iacob the Lab sessions of this course.
Intern supervisor, University of Cambridge, Department of Computer Science and Technology, 2023
I supervised Allen Cong during his Summer Internship. The project was related to optimising a CV task on a Rock64 Rock Pi 4 SE equipped with an Intel RealSense camera.
Master's course, University of Cambridge, Department of Computer Science and Technology, 2023
I run in coordination with Hongxiang Fan and Alexandru-Andrei Iacob the Lab sessions of this course.