4 papers
The Cost of Adaptation under Differential Privacy: Optimal Adaptive Federated Density Estimation
T. Tony Cai, Abhinav Chakraborty, Lasse Vuursteen
Privacy-preserving data analysis has become a central challenge in modern statistics. At the same time, a long-standing goal in statistics is the development of adaptive procedures…
Optimal Differentially Private Ranking from Pairwise Comparisons
T. Tony Cai, Abhinav Chakraborty, Yichen Wang
Data privacy is a central concern in many applications involving ranking from incomplete and noisy pairwise comparisons, such as recommendation systems, educational assessments, an…
Optimal Federated Learning for Functional Mean Estimation under Heterogeneous Privacy Constraints
Tony Cai, Abhinav Chakraborty, Lasse Vuursteen
Federated learning (FL) is a distributed machine learning technique designed to preserve data privacy and security, and it has gained significant importance due to its broad range…
Federated PCA and Estimation for Spiked Covariance Matrices: Optimal Rates and Efficient Algorithm
Jingyang Li, T. Tony Cai, Dong Xia +1
Federated Learning (FL) has gained significant recent attention in machine learning for its enhanced privacy and data security, making it indispensable in fields such as healthcare…