组合优化与强化学习：

[1] Fei Ni, Jianye Hao, Jiawen Lu, Xialiang Tong, Mingxuan Yuan, Jiahui Duan, Yi Ma, Kun He. A Multi-Graph Attributed Reinforcement Learning based Optimization Algorithm for Large-scale Hybrid Flow Shop Scheduling Problem. In Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021.

[2] Chu-Min Li and Zhenxing Xu, Jordi Coll, Felip Many{\`{a}}, Djamal Habet, Kun He. Combining Clause Learning and Branch and Bound for MaxSAT. In Proceedings of the International Conference on Principles and Practice of Constraint Programming, 2021.

[3] Jiongzhi Zheng, Kun He, Jianrong Zhou, Yan Jin, Chu-Min Li. Combining Reinforcement Learning with Lin-Kernighan-Helsgaun Algorithm for the Traveling Salesman Problem. In Proceedings of the AAAI Conference on Artificial Intelligence, 2021.

[3] Jianrong Zhou, Kun He, Jiongzhi Zheng, Chu-Min Li, Yanli Liu. A Strengthened Branch and Bound Algorithm for the Maximum Common (Connected) Subgraph Problem. In Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022.

[4] Jiongzhi Zheng, Kun He, Jianrong Zhou, Yan Jin, Chu-Min Li, Felip Many{\`{a}}. BandMaxSAT: A Local Search MaxSAT Solver with Multi-armed Bandit. In Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022.

[5] Jiongzhi Zheng, Kun He, Jianrong Zhou. Farsighted Probabilistic Sampling: A General Strategy for Boosting the Local Search Solvers for MaxSAT Problems. In Proceedings of the AAAI Conference on Artificial Intelligence, 2023.

对抗攻防：

[1] Chuanbiao Song, Kun He, Jiadong Lin, Liwei Wang, John E. Hopcroft. Robust Local Features for Improving the Generalization of Adversarial Training. In Proceedings of the 8th International Conference on Learning Representations, 2020.

[2] Jiadong Lin, Chuanbiao Song, Kun He, Liwei Wang, John E. Hopcroft. Nesterov Accelerated Gradient and Scale Invariance for Adversarial Attacks. In Proceedings of the 8th International Conference on Learning Representations, 2020.

[5] Xiaosen Wang, Xuanran He, Jingdong Wang, Kun He. Admix: Enhancing the Transferability of Adversarial Attacks. In Proceedings of the IEEE/CVF International Conference on Computer Vision, 2021.

[6] Xiaosen Wang, Kun He. Enhancing the Transferability of Adversarial Attacks Through Variance Tuning. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2021.

[7] Xinze Zhang, Junzhe Zhang, Zhenhua Chen, Kun He. Crafting Adversarial Examples for Neural Machine Translation. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021.

[8] Yifeng Xiong, Jiadong Lin, Min Zhang, John E. Hopcroft, Kun He. Stochastic Variance Reduced Ensemble Adversarial Attack for Boosting the Adversarial Transferability. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022.

[9] Xiaosen Wang, Zeliang Zhang, Kangheng Tong, Dihong Gong, Kun He, Zhifeng Li, Wei Liu. Triangle Attack: A Query-Efficient Decision-Based Adversarial Attack. In Proceedings of the European Conference on Computer Vision, 2022.

[10] Xiaosen, Wang, Kangheng Tong, and Kun He. "Rethinking the Backward Propagation for Adversarial Transferability." Advances in Neural Information Processing Systems 36, 2023.

社交网络与图数据挖掘:

[1] Qiuting He, Jinsong Chen, Hao Xu, Kun He. Structural Robust Label Propagation on Homogeneous Graphs. In Proceedings of the IEEE International Conference on Data Mining, 2022.

[2] Chao Li, Hao Xu, Kun He. Differentiable Meta Multigraph Search with Partial Message Propagation on Heterogeneous Information Networks. In Proceedings of the AAAI Conference on Artificial Intelligence, 2023.

[3] Jinsong Chen, Kaiyuan Gao, Gaichao Li, Kun He. NAGphormer: A Tokenized Graph Transformer for Node Classification in Large Graphs. In Proceedings of the Eleventh International Conference on Learning Representations, 2023.

[4] Meng Wang, Boyu Li, Kun He*, John E. Hopcroft. Uncovering the Local Hidden Community Structure in Social Networks. ACM Transactions on Knowledge Discovery from Data. 2023.

深度学习：

[1] Chao Li, Yixiao Yang, Kun He, Stephen Lin, John E. Hopcroft. Single Image Reflection Removal Through Cascaded Refinement. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020.

[2] Shuoxi Zhang, Hanpeng Liu, Stephen Lin, Kun He. You Only Need Less Attention Each Stage on Vision Transformers, in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2024.

[3] Chen Q, Li C, Ning J, et al. GMConv: Modulating Effective Receptive Fields for Convolutional Kernels[J]. IEEE Transactions on Neural Networks and Learning Systems, 2024.