Xiangxiang Xu(徐祥祥)


Ph.D. Candidate in Electronic Engineering, Tsinghua University

Email: xiangxiangxu AT ieee.org

Google Scholar, CV


My research focuses on the understanding of machine learning from the perspective of information theory, together with its applications in data analytics.

Recent works

  1. Shao-Lun Huang, Xiangxiang Xu, and Lizhong Zheng. An information-theoretic approach to unsupervised feature selection for high-dimensional data". In IEEE Journal on Selected Areas in Information Theory (2020).
  2. Xiangxiang Xu and Shao-Lun Huang. Maximal Correlation Regression. In: IEEE Access 8 (2020), pp. 26591-26601. [Paper]
  3. Shao-Lun Huang, Xiangxiang Xu, Lizhong Zheng, and Gregory W. Wornell. An Information Theoretic Interpretation to Deep Neural Networks. In IEEE International Symposium on Information Theory (ISIT), 2019. [Paper] [arXiv]
  4. Lichen Wang, Jiaxiang Wu, Shao-Lun Huang, Lizhong Zheng, Xiangxiang Xu, Lin Zhang, and Junzhou Huang. An Efficient Approach to Informative Feature Extraction from Multimodal Data. In AAAI 2019. [Paper] [arXiv]
  5. Xiangxiang Xu, Shao-Lun Huang, Lizhong Zheng, and Lin Zhang. The Geometric Structure of Generalized Softmax Learning. In 2018 IEEE Information Theory Workshop (ITW) (IEEE ITW 2018), Guangzhou, P.R. China, November 2018. [Paper] [Slides]