Welcome to my homepage!

I have finished my PhD in Machine Learning in The University of Edinburgh in the School of Informatics. My academic advisor is Amos Storkey. I am a member of the Institute for Adaptive and Neural Computation .
My research interest is between machine learning models and optimization, specially on how to apply stochastic methods and multi-agent mechanism into parallelising machine learning models to handle massive data. Recently I has been looking at fast methods for distributed optimization, and Langevin dynamics for large-scale Bayesian sampling.

I have moved to Beijing Institute of Big Data Research (BIBDR) after my Ph.D study.

Publications

  • Zhanxing Zhu and Amos Storkey. Stochastic Parallel Block Coordinate Descent for Large-scale Saddle Point Problems. AAAI 2016. [pdf to appear]
  • Zhanxing Zhu*, Xiaocheng Shang*, Benedict Leimkuhler and Amos Storkey. Covariance-Controlled Adaptive Langevin Thermostat for Large-Scale Bayesian Sampling. NIPS 2015 (* indicates equal contribution). [arXiv version]
  • Zhanxing Zhu and Amos Storkey. Adaptive Stochastic Primal-Dual Coordinate Descent for Separable Saddle Point Problems. ECML/PKDD 2015. [full arXiv version] [Publisher's website]
  • Amos J. Storkey, Zhanxing Zhu and Jinli Hu. Aggregation Under Bias: Renyi Divergence Aggregation and its Implementation via Machine Learning Markets. ECML/PKDD 2015. [Publisher's website]
  • Francesco Corona, Zhanxing Zhu, Amauri Holanda de Souza Júnior, Michela Mulas, Emanuela Muru, Lorenzo Sassu, Guilherme Barreto, and Roberto Baratti. ``Supervised Distance Preserving Projections: Applications in the quantitative analysis of diesel fuels and light cycle oils from NIR spectra." Journal of Process Control (2014) [Publisher's Website].
  • Amos Storkey, Zhanxing Zhu, Jinli Hu. A Continuum from Mixtures to Products: Aggregation under Bias. ICML 2014 Workshop on Divergence Methods for Probabilistic Inference. [pdf]
  • Zhanxing Zhu, Zhirong Yang and Erkki Oja. Multiplicative Updates for Learning with Stochastic Matrices. In the 18th Conference Scandinavian Conferences on Image Analysis (SCIA 2013), pages 143-152, Espoo, Finland, 2013.[pdf]
  • Zhanxing Zhu, Timo Simila and Francesco Corona. Supervised Distance Preserving Projection for Dimensionality Reduction. Neural Processing Letters 38(3): 445-463 (2013). [pdf]
  • Zhanxing Zhu, Francesco Corona, Amaury Lendasse, Roberto Baratti and Jose A. Romagnoli. Local linear models for soft-sensor design with application to an industrial deethanizer. 18th World Congress of the International Federation of Automatic Control (IFAC) , Milan, Italy, 2011.[pdf]
  • Zhirong Yang, Zhanxing Zhu and Erkki Oja. Automatic Rank Determination in Projective Nonnegative Matrix Factorization. 9th International Conference on Latent Variable Analysis and Signal Separation (LVA/ICA 2010).[pdf] [Code]

Contact

Room 2.25, Informatics Forum
10 Crichton Street
Edinburgh, UK. EH8 9AB
E-Mail: zhanxing.zhu #AT# ed.ac.uk OR zhanxing.zhu #AT# gmail.com

" Only in silence the word, only in dark the light, only in dying life: bright the hawk's flight on the empty sky. "
— Ursula K. Le Guin (A Wizard of Earthsea)