[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.
[3] 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.
[4] 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.
[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] Haohai Sun, Jialun Zhong, Yunpu Ma, Zhen Han, Kun He. TimeTraveler: Reinforcement Learning for Temporal Knowledge Graph Forecasting. In Proceedings of the Conference on Empirical Methods in Natural Language Processing, 2021.
[7] 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.
[8] 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.
[9] 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.
[10] 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.
[11] 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.
[12] 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.
[13] 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.
[14] 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.
[15] 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.
[16] 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.
[17] 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.
[18] Chuanbiao Song#,Yanbo Fan#, Aoyang Zhou#, Baoyuan Wu*, Yiming Li, Zhifeng Li, Kun He*. Regional adversarial training for better robust generalization[J]. International Journal of Computer Vision, 2024.