Secure & Private Federated Neuroimaging

no code implementations • 11 May 2022 • Dimitris Stripelis, Umang Gupta, Hamza Saleem, Nikhil Dhinagar, Tanmay Ghai, Rafael Chrysovalantis Anastasiou, Armaghan Asghar, Greg Ver Steeg, Srivatsan Ravi, Muhammad Naveed, Paul M. Thompson, Jose Luis Ambite

Each site trains the neural network over its private data for some time, then shares the neural network parameters (i. e., weights, gradients) with a Federation Controller, which in turn aggregates the local models, sends the resulting community model back to each site, and the process repeats.

Federated Learning

MetisFL: An Embarrassingly Parallelized Controller for Scalable & Efficient Federated Learning Workflows

no code implementations • 1 Nov 2023 • Dimitris Stripelis, Chrysovalantis Anastasiou, Patrick Toral, Armaghan Asghar, Jose Luis Ambite

The controller is responsible for managing the execution of FL workflows across learners and the learners for training and evaluating federated models over their private datasets.

Federated Learning Scheduling