HybridAlpha: An Efficient Approach for Privacy-Preserving Federated Learning
HybridAlpha: An Efficient Approach for Privacy-Preserving Federated Learning
Federated learning has emerged as a promising approach for collaborative and privacy-preserving learning. Participants in a federated learning process cooperatively train a model by exchanging model parameters instead of the actual training data, which they might want to keep private. However, parameter interaction and the resulting model still might disclose …