Oxford-Tencent Collaboration on Large Scale Machine Learning

This project involving Yee Whye Teh and Dino Sejdinovic aims to explore novel methods for machine learning, with particular foci on deep generative models and hyperparameter optimization. There will be several topics of investigation in these fields that will cut across various aspects of large-scale machine learning: efficient computation for working large datasets; scalable and expressive models that can extract as much information as possible from the available data; large-scale and heterogeneous computational substrates (e.g. GPUs, multicore systems, networked clusters) and theoretical foundations. The project is funded by Tencent AI Lab.



  • J. Chen , J. Zhu , Y. W. Teh , T. Zhang , Stochastic Expectation Maximization with Variance Reduction, in Advances in Neural Information Processing Systems (NeurIPS), 2018, 7978–7988.
    Project: bigbayes, tencent-lsml
  • H. Law , P. Zhao , J. Huang , D. Sejdinovic , Hyperparameter Learning via Distributional Transfer, Meta-Learning workshop, NeurIPS, 2018.
    Project: tencent-lsml