no code implementations • 26 Jan 2021 • Thomas B. Berrett, Richard J. Samworth
We present the $U$-Statistic Permutation (USP) test of independence in the context of discrete data displayed in a contingency table.
no code implementations • NeurIPS 2020 • Thomas B. Berrett, Cristina Butucea
We construct efficient randomized algorithms and test procedures, in both the case where only non-interactive privacy mechanisms are allowed and also in the case where all sequentially interactive privacy mechanisms are allowed.
no code implementations • 15 Jan 2020 • Thomas B. Berrett, Ioannis Kontoyiannis, Richard J. Samworth
We study the problem of independence testing given independent and identically distributed pairs taking values in a $\sigma$-finite, separable measure space.
no code implementations • 18 Apr 2019 • Thomas B. Berrett, Richard J. Samworth
One interesting consequence of our results is the discovery that, for certain functionals, the worst-case performance of our estimator may improve on that of the natural `oracle' estimator, which is given access to the values of the unknown densities at the observations.
no code implementations • 14 Jul 2018 • Thomas B. Berrett, Yi Wang, Rina Foygel Barber, Richard J. Samworth
Like the conditional randomization test of Cand\`es et al. (2018), our test relies on the availability of an approximation to the distribution of $X \mid Z$.
Methodology Statistics Theory Statistics Theory
no code implementations • 17 Nov 2017 • Thomas B. Berrett, Richard J. Samworth
We propose a test of independence of two multivariate random vectors, given a sample from the underlying population.
no code implementations • 3 Apr 2017 • Timothy I. Cannings, Thomas B. Berrett, Richard J. Samworth
We derive a new asymptotic expansion for the global excess risk of a local-$k$-nearest neighbour classifier, where the choice of $k$ may depend upon the test point.