2 citations · 5 across the 8 of their papers we have counts for
9 papers
Learning Sparse Support under Differential Privacy: Adaptive Algorithms and Minimax Limits
Jia Gu, T. Tony Cai
We study exact support recovery under -differential privacy in sparse high-dimensional linear regression. We introduce Saturated Propose-test-release, a general mechanism th…
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…
Minimax And Adaptive Transfer Learning for Nonparametric Classification under Distributed Differential Privacy Constraints
Arnab Auddy, T. Tony Cai, Abhinav Chakraborty
This paper considers minimax and adaptive transfer learning for nonparametric classification under the posterior drift model with distributed differential privacy constraints. Our…
Optimal Federated Learning for Nonparametric Regression with Heterogeneous Distributed Differential Privacy Constraints
T. Tony Cai, Abhinav Chakraborty, Lasse Vuursteen
This paper studies federated learning for nonparametric regression in the context of distributed samples across different servers, each adhering to distinct differential privacy co…
Federated Nonparametric Hypothesis Testing with Differential Privacy Constraints: Optimal Rates and Adaptive Tests
T. Tony Cai, Abhinav Chakraborty, Lasse Vuursteen
Federated learning has attracted significant recent attention due to its applicability across a wide range of settings where data is collected and analyzed across disparate locatio…
Optimal Differentially Private PCA and Estimation for Spiked Covariance Matrices
T. Tony Cai, Dong Xia, Mengyue Zha
Estimating a covariance matrix and its associated principal components is a fundamental problem in contemporary statistics. While optimal estimation procedures have been developed…