Sparsity-preserving differentially private training – Google

Marginal-based Methods for Differentially Private Synthetic Data

Towards provably efficient quantum algorithms for large-scale

Shifting machine learning for healthcare from development to

An elaboration of privacy-protected graph perturbation. Left: we

Sparsity-preserving differentially private training – Google

Secure sparse matrix multiplication. For details on the

Privacy-preserving Analytics and Data Mining at LinkedIn

Preserving fairness and diagnostic accuracy in private large-scale

Sparsity-preserving differentially private training – Google

Future Internet, Free Full-Text

The Private Aggregation of Teacher Ensembles (PATE) mechanism

Generalized genomic data sharing for differentially private

On Privacy and Personalization in Federated Learning: A