Differential Privacy (DP) ensures that training a machine learning model...
Machine learning models are increasingly used in high-stakes decision-ma...
We study differentially private (DP) stochastic optimization (SO) with d...
We study differentially private (DP) federated learning (FL) with non-co...
Federated learning (FL) is a distributed learning paradigm in which many...
In this paper, we propose a new notion of fairness violation, called
Exp...
Finding efficient, easily implementable differentially private (DP)
algo...