Below is a selected collection of my publications. A full list can be found at my Google Scholar profile.
- Xu, Xiangxiang and Lizhong Zheng. Multiuser Detection With Neural Feature Learning. 2024 IEEE Military Communications Conference (MILCOM 2024).
- Xu, Xiangxiang and Lizhong Zheng. Dependence Induced Representations. 2024 60th Annual Allerton Conference on Communication, Control, and Computing (Allerton).
- Xu, Xiangxiang and Lizhong Zheng. Neural Feature Learning in Function Space. Journal of Machine Learning Research (JMLR), 25(142), 2024. [Code]
- Ryu, J. Jon, Xiangxiang Xu, H. S. Erol, Yuheng Bu, Lizhong Zheng, and Gregory W. Wornell. Operator SVD with Neural Networks via Nested Low-Rank Approximation. ICML, 2024. [Code] [Poster]
- Xu, Xiangxiang, Lizhong Zheng, and Ishank Agrawal. Neural Feature Learning for Engineering Problems. 2023 59th Annual Allerton Conference on Communication, Control, and Computing (Allerton).
- Xu, Xiangxiang and Lizhong Zheng. Sequential Dependence Decomposition and Feature Learning. 2023 59th Annual Allerton Conference on Communication, Control, and Computing (Allerton). [Slides] [Demo]
- Xu, Xiangxiang and Lizhong Zheng. Kernel Subspace and Feature Extraction. 2023 IEEE International Symposium on Information Theory (ISIT). IEEE. 2023, pp. 1032–1037. [Slides]
- Xu, Xiangxiang and Shao-Lun Huang. On Distributed Learning with Constant Communication Bits. In IEEE Journal on Selected Areas in Information Theory (2022). [Slides]
- 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. [Code]
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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). [Appendix]
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Xu, Xiangxiang and Shao-Lun Huang. Maximal Correlation Regression. In: IEEE Access 8 (2020), pp. 26591-26601. [Code]
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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. [Slides] [Code]