Papers
Below one can find my working papers, preprints and published papers.
Working papers
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Optimal private high-dimensional distributed testing – T. Tony Cai, Abhinav Chakraborty and Lasse Vuursteen
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A debiased semiparametric Bernstein von Mises theorem for linear regression – Ismael Castillo, Stephanié van der Pas, Kolyan Ray, and Aad van der Vaart, Lasse Vuursteen
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A Bayesian approach to multi-view Learning – Lasse Vuursteen, Timo van der Poel, Wouter van Loon, Botond Szabo, Marjolein Fokkema, Mark de Rooij
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Convergence rates for nonparametric averaged distributed M-estimators and Gaussian process priors – Botond Szabo, Lasse Vuursteen
Under review
- Optimal federated learning for nonparametric regression with ongoing heterogenous distributed differential privacy constraints – T. Tony Cai, Abhinav Chakraborty and Lasse Vuursteen
Published
2023
- Optimal testing using combined test statistics across independent studiesIn Thirty-seventh Conference on Neural Information Processing Systems, 2023