Xiangxiang Xu


Postdoctoral Researcher, EECS, MIT


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Selected Publications

  1. Xu, Xiangxiang, Shao-Lun Huang, Lizhong Zheng, and Gregory W. Wornell. 2022. "An Information Theoretic Interpretation to Deep Neural Networks" Entropy 24, no. 1: 135. [Link] [Code]
  2. Xu, Xiangxiang and Shao-Lun Huang. On Distributed Hypothesis Testing with Constant-Bit Communication Constraints. In 2021 IEEE Information Theory Workshop (IEEE ITW 2021). [Paper] [Slides]
  3. Xu, Xiangxiang and Shao-Lun Huang. An Information Theoretic Framework for Distributed Learning Algorithms. In IEEE International Symposium on Information Theory (ISIT), 2021. [Paper] [Slides]
  4. Huang, Shao-Lun, 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). [Link]
  5. Xu, Xiangxiang and Shao-Lun Huang. Maximal Correlation Regression. In: IEEE Access 8 (2020), pp. 26591-26601. [Paper] [Code]
  6. Wang, Lichen, 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]
  7. Xu, Xiangxiang, 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] [Code]