Papers | Lasse Vuursteen

Working papers

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
Optimal private high-dimensional distributed testing – T. Tony Cai, Abhinav Chakraborty and Lasse Vuursteen
A Bayesian approach to multi-view Learning – Lasse Vuursteen, Timo van der Poel, Wouter van Loon, Botond Szabo, Marjolein Fokkema, Mark de Rooij
Convergence rates for nonparametric averaged distributed M-estimators and Gaussian process priors – Botond Szabo, Lasse Vuursteen

Under review

Optimal high-dimensional and nonparametric distributed testing under communication constraints (2022) – preprint – Botond Szabó, Lasse Vuursteen, Harry Van Zanten

Published

2022

IEEE

Optimal Distributed Composite Testing in High-dimensional Gaussian Models with 1-bit Communication

Botond Szabó, Lasse Vuursteen, and Harry van Zanten

IEEE Transactions on Information Theory, 2022

Bib Website

@article{szabo2022optimal,
  title = {Optimal Distributed Composite Testing in High-dimensional Gaussian Models with 1-bit Communication},
  author = {Szab{\'o}, Botond and Vuursteen, Lasse and Zanten, Harry van},
  journal = {IEEE Transactions on Information Theory},
  url = {https://ieeexplore.ieee.org/document/9709332},
  year = {2022},
  volume = {68},
  number = {6},
  pages = {4070-4084},
  doi = {10.1109/TIT.2022.3150599},
  publisher = {IEEE}
}