Search Results for author:
Found 2 papers, 1 papers with code
Backpropagation Clipping for Deep Learning with Differential Privacy
We present backpropagation clipping, a novel variant of differentially private stochastic gradient descent (DP-SGD) for privacy-preserving deep learning.
Efficient Differentially Private Secure Aggregation for Federated Learning via Hardness of Learning with Errors
Federated machine learning leverages edge computing to develop models from network user data, but privacy in federated learning remains a major challenge.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
