Profile

Dr. Xi Yang is currently a lecturer in Xi’an Jiaotong-Liverpool University. She received the Ph.D. degree, B.Sc. degree and M.Sc. degree with distinction from the University of Liverpool, Liverpool, U.K.. Her research interests lie in the field of Bayesian probabilistic approaches to machine learning, pattern recognition and data mining. Her publications can be founded via Google Scholar.
Xi Yang
  • Qualifications

    • Ph.D. in Electrical Engineering and Electronics, University of Liverpool
    • M.Sc in Adv. Computer Science with Internet Econ. , University of Liverpool
    • B.Sc in Mathematics with Finance, University of Liverpool
  • Experience

    • 2019~present: Lecturer, Department of CSSE, XJTLU, China.
  • Research interests

    • Bayesian probabilistic approaches to machine learning, pattern recognition and data mining
  • Articles

    • Xi Yang, Kaizhu Huang, Rui Zhang, John Y. Goulermas, “A Novel Deep Density Model for Unsupervised Learning,” Cognitive Computation, pp. 1-11, 2018.
    • Xi Yang, Kaizhu Huang, Rui Zhang, John Y. Goulermas, Amir Hussain, “A New Two-layer Mixture of Factor Analyzers with Joint Factor Loading Model for the Classification of Small Dataset Problems,” Neurocomputing, vol. 312, pp. 352-363, 2018.
    • Xi Yang, Kaizhu Huang, Rui Zhang, Amir Hussain, “Learning Latent Features with Infinite Non-negative Binary Matrix Tri-factorisation,” IEEE Transactions on Emerging Topics in Computational Intelligence, vol. 2, no. 3, 2018.
    • Xi Yang, Kaizhu Huang, John Y. Goulermas, Rui Zhang, “Joint Learning of Unsupervised Dimensionality Reduction and Gaussian Mixture Model,” Neural Processing Letters, vol. 45, no. 3, pp. 791 − 806, 2017.
  • Proceedings

    • X. Yang, Y. Yan, K. Huang and R. Zhang,"VSB-DVM: An End-to-end Bayesian Nonparametric Generalization of Deep Variational Mixture Model," in International Conference of Data Mining, 2019.
    • Xi Yang, Kaizhu Huang, Rui Zhang, "Deep Mixtures of Factor Analyzers with Common Loadings: A Novel Deep Generative Approach to Clustering," in Proceedings of International Conference on Neural Information Processing, Springer, 2017, pp. 709-719.
    • Xi Yang, Kaizhu Huang, Rui Zhang, Amir Hussain, “Learning Latent Features with Infinite Non-negative Binary Matrix Tri-factorisation,” in Proceedings of International Conference on Neural Information Processing, Springer, 2016, pp. 587-596.
    • Xi Yang, Kaizhu Huang, Rui Zhang, John Y. Goulermas, “Two-layer Mixture of Factor Analysers with Joint Factor Loading,” in Proceedings of International Joint Conference on Neural Networks, IEEE, 2015, pp. 18
    • Xi Yang, Kaizhu Huang, Rui Zhang, “Unsupervised Dimensionality Reduction for Gaussian Mixture Model,” in Proceedings of International Conference on Neural Information Processing, Springer, 2014, pp. 84-92.
  • Chapters, cases, readings and supplements

    • Yang X, Huang K, Zhang R, et al. Introduction to Deep Density Models with Latent Variables[M]//Deep Learning: Fundamentals, Theory and Applications. Springer, Cham, 2019: 1-29.
  • Courses taught

    • CSE 409 Cloud Computing
  • Telephone

    +86 (0)512 88161506
  • Email

    Xi.Yang@xjtlu.edu.cn
  • Address

    SD543, XJTLU
    Suzhou Dushu Lake Science and Education Innovation District
    Suzhou Industrial Park
    Suzhou
    P.R.China
    215123