Scalable federated machine learning with FEDn
Published: May 1, 2022
Abstract
Federated machine learning promises to overcome the input privacy challenge in machine learning. By iteratively updating a model on private clients and aggregating these local model updates into a global federated model, private data is incorporated in the federated model without needing to share and expose that data. Several open software projects for federated learning have appeared. Most of them focuses on supporting flexible experimentation...
Paper Details
Title
Scalable federated machine learning with FEDn
Published Date
May 1, 2022
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