research
Working papers
-
The cost of adaptation under differential privacy (working title) — T. Tony Cai, Abhinav Chakraborty, and Lasse Vuursteen
-
A debiased semiparametric Bernstein–von Mises theorem for linear regression — Ismaël Castillo, Stéphanie van der Pas, Kolyan Ray, Aad van der Vaart, and Lasse Vuursteen
-
A Bayesian approach to multi-view learning — Lasse Vuursteen, Timo van der Poel, Wouter van Loon, Botond Szabó, Marjolein Fokkema, and Mark de Rooij
Under review
-
Optimal Federated Learning for Functional Mean Estimation under Heterogeneous Privacy Constraints — T. Tony Cai, Abhinav Chakraborty, and Lasse Vuursteen
-
Optimal federated learning for nonparametric regression with ongoing heterogeneous distributed differential privacy constraints — T. Tony Cai, Abhinav Chakraborty, and Lasse Vuursteen
-
Federated Nonparametric Hypothesis Testing with Differential Privacy Constraints: Optimal Rates and Adaptive Tests — T. Tony Cai, Abhinav Chakraborty, and Lasse Vuursteen
Published
2024
- NeuRIPSOptimal Private and Communication Constraint Distributed Goodness-of-Fit Testing for Discrete Distributions in the Large Sample RegimeTo appear in Thirty-seventh Conference on Neural Information Processing Systems, 2024
2023
- NeuRIPSOptimal testing using combined test statistics across independent studiesIn Thirty-sixth Conference on Neural Information Processing Systems, 2023