1. Hong Chen, Youcheng Fu, Xue Jiang, Yanhong Chen, Weifu Li, Yicong Zhou, Feng Zheng. Gradient Learning with the Mode-induced Loss: Consistency Analysis and Applications. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2023.

2. Yuxiang Han, Hong Chen, Tieliang Gong, Jia Cai. Robust Partially Linear Models for Automatic Structure Discovery, Expert Systems with Applications, Volume 217, 1 May 2023, 119528

3. Linqian Han, Wanshun Zhong, Jia Qian, Minliang Jin, Peng Tian, Wanchao Zhu, Hongwei Zhang, Yonghao Sun, Jia-Wu Feng, Xiangguo Liu, Guo Chen, Babar Farid, Ruonan Li, Zimo Xiong, Zhihui Tian, Juan Li, Zi Luo, Dengxiang Du, Sijia Chen, Qixiao Jin, Jiaxin Li, Zhao Li, Yan Liang, Xiaomeng Jin, Yong Peng, Chang Zheng, Xinnan Ye, Yuejia Yin, Hong Chen, Weifu Li, Ling-Ling Chen, Qing Li, Jianbing Yan, Fang Yang & Lin Li. A multi-omics integrative network map of maize, Nature Genetics, 2023.

4. Yulong Wang, Kit Ian Kou, Hong Chen, Yuan Yan Tang, Luoqing Li. Simultaneous Robust Matching Pursuit for Multi-view Learning, Pattern Recognition,Volume 134:109100, 2023.

5. Yulong Wang, Yap-Peng Tan, Yuan Yan Tang, Hong Chen, Cuiming Zou, Luoqing Li. Generalized and Discriminative Collaborative Representation for Multiclass Classification, IEEE Transactions on Cybernetics,52(5):2675–2686, 2022.

6. Tieliang Gong, Yuxin Dong, Hong Chen, Bo Dong, Chen Li. Markov Subsampling Based on Huber Criterion. IEEE Transactions on Neural Networks and Learning Systems, doi: 10.1109/TNNLS.2022.3189069, 2022.

7. Jun Chen, Hao Deng, Shuxin Li, Weifu Li, Hong Chen, Yanhong Chen, Bingxian Luo. RU-net: A Residual U-net for Automatic Interplanetary Coronal Mass Ejection Detection. The Astrophysical Journal Supplement Series, 259(1):8, 2022.

8. Hong Chen, Yingjie Wang, Feng Zheng, Cheng Deng, Heng Huang. Sparse modal additive model. IEEE Transactions on Neural Networks and Learning Systems, 32(6): 2373-2387, 2021.

9. Hong Chen, Changying Guo,Yingjie Wang, Huijuan Xiong. Sparse additive machine with ramp loss. Analysis and Applications, 19(3):509-528, 2021.

10. Yulong Wang, Yuan Yan Tang, Luoqing Li, Hong Chen. Modal regression based atomic representation for robust face recognition and reconstruction, IEEE Transactions on Cybernetics,50(10):4393–4405, 2020.

11. Yulong Wang,Yuan-Yan Tang, Luoqing Li, Hong Chen, Jianjia Pan. Atomic representation-based classification: theory, algorithm and applications, IEEE Transactions on Pattern Analysis and Machine Intelligence, 41(1): 6–19, 2019.

12. Xiaoqian Wang, Hong Chen, Jingwen Yan, Kwangsik Nho, Shannon L Risacher, Andrew J Saykin, Li Shen, Heng Huang. Quantitative trait loci identification for brain endophenotypes via new additive model with random networks, Bioinformatics, 34(17): i866–i874, 2018.

13. Hong Chen, Yulong Wang. Kernel-based sparse regression with the correntropy-induced loss, Applied and Computational Harmonic Analysis, 44(1): 144–164, 2018.

14. Tieliang Gong, Zongben Xu, Hong Chen. Generalization analysis of Fredholm kernel regularized classifiers, Neural Computation, 29(7): 1879–1901, 2017.

15. Yicong Zhou#, Hong Chen#, Rushi Lan, Zhibin Pan. Generalization performance of regularized ranking with multiscale kernels, IEEE Transactions on Neural Networks and Learning Systems, 27: 993-1002, 2016. (#contributed equally)

16. Hong Chen, Jiangtao Peng, Yicong Zhou, Luoqing Li, Zhibin Pan. Extreme learning machine for ranking: Generalization analysis and applications, Neural Networks, 53: 110-126, 2014.

17. Hong Chen, Yi Tang, Luoqing Li, Yuan Yuan, Xuelong Li,Yuan Yan Tang, Error analysis of stochastic gradient descent ranking, IEEE Transactions on Cybernetics, 43: 898–909, 2013.

18. Hong Chen, Zhibin Pan, Luoqing Li, Yuan Yan Tang. Error analysis of coefficient-based regularized algorithm for density-level detection, Neural Computation, 25(4): 1107–1121, 2013.

19. Hong Chen, Yicong Zhou, Yuan Yan Tang, Luoqing Li, Zhibin Pan, Convergence rate of semi-supervised greedy algorithm, Neural Networks, 44–50, 2013.

20. Hong Chen. The convergence rate of a regularized ranking algorithm, Journal of Approximation Theory, 164: 1513–1519, 2012.

21. Hong Chen, Luoqing Li, Jiangtao Peng. Semi-supervised learning based on high density regions estimation, Neural Networks, 23(7): 812–818, 2010.

22. Hong Chen, Luoqing Li. Semi-supervised multi-category classification with imperfect model, IEEE Transactions on Neural Networks, 20(10): 1594–1603, 2009.