我是华中农业大学信息学院的博士研究生，由陈洪教授指导。我于2021年在湖北工业大学获得了理学学士学位。随后，在李伟夫副教授的指导下攻读数学硕士学位。我的研究领域集中在学习理论，特别关注以下主题：

（1）核积分算子理论

（2）成对学习理论

（3）非独立同分布样本的集中不等式。

目前发表以下工作：

1. Liyuan Liu, Yaohui Chen, Weifu Li, Yingjie Wang, Bin Gu, Feng Zheng, Hong Chen. Generalization Bounds of Deep Neural Networks With τ-Mixing Samples. IEEE Transactions on Neural Networks and Learning Systems, 2025.

2. Liyuan Liu, Hong Chen, Chi Xiao, Weifu Li. The Consistency Analysis of Gradient Learning under Independent Covariate Shift. Neurocomputing, 2025.

3. Liyuan Liu, Hong Chen, Weifu Li, Tieliang Gong, Hao Deng, Yulong Wang. Trajectory-Dependent Generalization Bounds for Pairwise Learning with φ-Mixing Samples. IJCAI-2025.

4. Liyuan Liu, Biqin Song, Zhibin Pan, Chuanwu Yang, Chi Xiao, Weifu Li. Gradient Learning under Tilted Empirical Risk Minimization. Entropy, 2022.

5. 刘力源, 张学林, 陈洪, 李伟夫, 廖健华, 解凯东, 伍小萌, 陈耀辉. 基于YOLOv11-FS模型的柑橘花粉活力率检测. 华中农业大学学报, 2025.

6. Zhihao Li, Xue Jiang, Liyuan Liu, Xuelin Zhang, Hong Chen, Feng Zheng. On the Generalization Ability of Next-Token-Prediction Pretraining. ICML-2025.

7. Junlong Pan, Weifu Li, Liyuan Liu, Kang Jia, Tong Liu, Fen Chen. Variable Selection Using Deep Variational Information Bottleneck with Drop-Out-One Loss. Applied Sciences, 2023.

8. Jingyi Chen, Xuelin Zhang, Peipei Yuan, Liyuan Liu, Hong Chen. Distribution-Aware Neural Additive Models. ICASSP, 2026.

9. Richeng Zhou, Xuelin Zhang, Hong Chen, Weifu Li, Liyuan Li. Pairwise Generalized Importance Weighting for Metric Learning under Distribution Shift. ICPADS-2025.