Ho Chung Leon Law

Ho Chung Leon Law

Kernel methods, machine learning

Leon was a DPhil student in the OxWaSP program, supervised by Professor Dino Sejdinovic and Dr Christopher Yau. His research interests lie in kernel methods, Gaussian processes, and Bayesian optimisation. Leon graduated in 2019 with the thesis entitled Testing and Learning on Distributional and Set Inputs.



  • H. Law , P. Zhao , L. Chan , J. Huang , D. Sejdinovic , Hyperparameter Learning via Distributional Transfer, Advances in Neural Information Processing Systems (NeurIPS), to appear, 2019.
    Project: tencent-lsml
  • A. Raj , H. Law , D. Sejdinovic , M. Park , A Differentially Private Kernel Two-Sample Test, in European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD), 2019, to appear.
    Project: bigbayes


  • H. Law , D. Sejdinovic , E. Cameron , T. Lucas , S. Flaxman , K. Battle , K. Fukumizu , Variational Learning on Aggregate Outputs with Gaussian Processes, in Advances in Neural Information Processing Systems (NeurIPS), 2018, to appear.
    Project: bigbayes
  • H. Law , D. Sutherland , D. Sejdinovic , S. Flaxman , Bayesian Approaches to Distribution Regression, in Artificial Intelligence and Statistics (AISTATS), 2018.
    Project: bigbayes


  • H. Law , C. Yau , D. Sejdinovic , Testing and Learning on Distributions with Symmetric Noise Invariance, in Advances in Neural Information Processing Systems (NeurIPS), 2017, 1343–1353.