Qinyi Zhang

Qinyi Zhang

Statistical Machine Learning, Kernel Method, Nonparametric Association Measures

Qinyi was a DPhil student supervised by Dino Sejdinovic and Sarah Filippi. Her research interests lie in large scale nonparametric association measures, in particular, those based on representations of probability distributions in the reproducing kernel Hilbert spaces (RKHSs). Nonparametric association of independence, conditional independence and multivariate interactions are all of interests. Qinyi has also been working on Bayesian nonparametric testing utilising distance measures in the RKHS.

Qinyi graduated in 2020 with the thesis entitled Kernel Based Hypothesis Tests: Large-Scale Approximations and Bayesian Perspectives.

Publications

2018

  • Q. Zhang , S. Filippi , A. Gretton , D. Sejdinovic , Large-Scale Kernel Methods for Independence Testing, Statistics and Computing, vol. 28, no. 1, 113–130, Jan. 2018.
    Project: bigbayes

2017

  • Q. Zhang , S. Filippi , S. Flaxman , D. Sejdinovic , Feature-to-Feature Regression for a Two-Step Conditional Independence Test, in Uncertainty in Artificial Intelligence (UAI), 2017.
    Project: bigbayes