学术及科研成果、专利、论文

代表性论文：

1. Jing, K., Khalili, A., Xu, C. (2025) Class-specific Joint Feature Screening for Ultrahigh-dimensional Mixture Regressions. Journal of the American Statistical Association. In press.
2. Li, X.  and Xu, C. (2024) Feature Screening with Conditional Rank Utility for Big-data Classification. Journal of the American Statistical Association, 119, 1385-1395.
3. Xu, C., Xu, W, Jing, K. (2023) Fast Algorithms for Singular Value Decomposition and Inverse of Nearly Low-rank Matrices. National Science Review, 10(6), 1-4.
4. Yang, S., Zhang, L., Yu, H., Xu, C., Fan, J., Xu, Z. (2022) Massive Data Clustering by Multi-scale Psychological Observations. National Science Review, 9(2), 1-9.
5. Zou, B., Jiang, H., Xu, C., Xu, J., You, X. Tang, Y. (2022) Learning Performance of Weighted Distributed Learning with Support Vector Machines. IEEE Transactions on Cybernetics, 53, 4630-4641.
6. Xia, Z., Chen, Y. and Xu, C. (2022) Multiview PCA: A Methodology of Feature Extraction and Dimension Reduction for High-order Data. IEEE Transactions on Cybernetics, 52, 11068-11080.
7. Zhang, F., Wang, J. Wang, W. and Xu, C. (2021) Low-tubal-rank plus Sparse Tensor Recovery with Prior Subspace Information. IEEE Transactions on Pattern Analysis and Machine Intelligence, 43, 3492-3507.
8. Zhou. T., Zhu, L., Xu, C. and Li, R. (2020) Model-free Forward Regression via Cumulative Divergence. Journal of the American Statistical Association, 115, 1393-1405.
9. Li, X., Li, R., Xia, Z. and Xu, C. (2020) Distributed Feature Screening via Componentwise Debiasing. Journal of Machine Learning Research, 21, 1-32.
10. Gong, T., Xi, Q., Xu, C. (2020) Robust Gradient-based Markov Subsampling. The Thirty-Fourth AAAI Conference on Artificial Intelligence. New York.
11. Xu, J., Xu, C., Zou, B., Tang Y., Peng, J. You, X. (2019) New Incremental Learning Algorithm with Support Vector Machines. IEEE Transactions on Systems, Man and Cybernetics: Systems, 49, 2230-2241.
12. Wang, J., Xu, C., Yang, X. and Zurada, J. (2018) A Novel Pruning Algorithm for Smoothing Feed-forward Neural Networks based on Group Lasso. IEEE Transactions on Neural Networks and Learning Systems, 29, 2012-2024.
13. Zou, B., Xu, C., Lu, Y., Tang, Y., Xu, J. and You, X. (2018). K-Times Markov Sampling for SVMC. IEEE Transactions on Neural Networks and Learning Systems, 29, 1328-1341.
14. Xu, C., Zhang, Y., Li, R. and Wu, X. (2016). On the Feasibility of Distributed Kernel Regression for Big Data. IEEE Transactions on Knowledge and Data Engineering, 28, 3041 - 3052.
15. Xu, C. and Chen, J. (2014). The Sparse MLE for Ultra-high-dimensional Feature Screening. Journal of the American Statistical Association, 109, 1257-1269.

 软件：

Zang, Q., Xu, C. and Burkett, K. (2025) SMLE: Joint Feature Screening via Sparse MLE. R package version 2.2-2.   下载链接