no code implementations • 21 Jul 2023 • Daniel Madrigal Diaz, Andre Manoel, Jialei Chen, Nalin Singal, Robert Sim
Federated learning enables model training across devices and silos while the training data remains within its security boundary, by distributing a model snapshot to a client running inside the boundary, running client code to update the model, and then aggregating updated snapshots across many clients in a central orchestrator.
1 code implementation • 25 Mar 2022 • Mirian Hipolito Garcia, Andre Manoel, Daniel Madrigal Diaz, FatemehSadat Mireshghallah, Robert Sim, Dimitrios Dimitriadis
We compare the platform with other state-of-the-art platforms and describe available features of FLUTE for experimentation in core areas of active research, such as optimization, privacy, and scalability.