Search Results for author:
Found 2 papers, 1 papers with code
Secure Aggregation for Federated Learning in Flower
Federated Learning (FL) allows parties to learn a shared prediction model by delegating the training computation to clients and aggregating all the separately trained models on the server.
Flower: A Friendly Federated Learning Research Framework
Federated Learning (FL) has emerged as a promising technique for edge devices to collaboratively learn a shared prediction model, while keeping their training data on the device, thereby decoupling the ability to do machine learning from the need to store the data in the cloud.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
