代表性论文：
[1]. Jifeng Hu, Yanchao Sun, Hechang Chen, Sili Huang, Haiyin Piao, Yi Chang, Lichao Sun. Distributional Reward Estimation for Effective Multi-agent Deep Reinforcement Learning. In Proceedings of the International Conference on the Advances in Neural Information Processing Systems (NeurIPS’22), New Orleans, USA, Nov 28-Dec 9, 35, (2022): 12619-12632. (CCF A)
[2]. Huang, Sili, Yanchao Sun, Jifeng Hu, Siyuan Guo, Bo Yang, Hechang Chen, Yi Chang, Lichao Sun. Learning Generalizable Agents via Saliency-Guided Features Decorrelation. Advances in Neural Information Processing Systems (NeurIPS’23), New Orleans, USA, Dec 10-16, 36, (2023): 13524-13537. (CCF A)
[3]. Siyuan Guo, Cheng Deng, Ying Wen, Hechang Chen, Yi Chang, Jun Wang. DS-Agent: Automated Data Science
by Empowering Large Language Models with Case-Based Reasoning. The Forty-first International Conference on Machine Learning (ICML’24), Vienna, Austria, Jul 21-Jul 27, 2024. (CCF A)
[4]. Sili Huang, Jifeng Hu, Hechang Chen, Lichao Sun, Bo Yang. In-Context Reinforcement Learning with Hierarchical Chain of Experience. The Forty-first International Conference on Machine Learning (ICML’24), Vienna, Austria, Jul 21-Jul 27, 2024. (CCF A)
[5]. Siyuan Guo, Lixin Zou, Hechang Chen, Bohao Qu, Haotian Chi, Philip S. Yu, Yi Chang. Sample Efficient Offline-to-Online Reinforcement Learning. IEEE Transactions on Knowledge and Data Engineering (TKDE), 2023, 36(3), pp: 1299-1310. (CCF A)
[6]. Xinqi Du, Ziyue Li, Cheng Long, Yongheng Xing, Philip S. Yu, Hechang Chen. FELight: Fairness-Aware Traffic Signal Control via Sample-Efficient Reinforcement Learning. IEEE Transactions on Knowledge and Data Engineering (TKDE), 2024, pp: 1-12. (CCF A)
[7]. Fan Li, Xu Si, Shisong Tang, Dingmin Wang, Kunyan Han, Bing Han, Guorui Zhou, Yang Song, Hechang Chen. Contextual Distillation Model for Diversified Recommendation. The 30th SIGKDD Conference on Knowledge Discovery and Data Mining (KDD’24), Barcelona, Spain, Aug 25-Aug 29, 2024. (CCF A)
[8]. Siyuan Guo, Lixin Zou, Yiding Liu, Wenwen Ye, Suqi Cheng, Shuaiqiang Wang, Hechang Chen, Dawei Yin, Yi chang. Enhanced Doubly Robust Learning for Debiasing Post-Click Conversion Rate Estimation. In Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR’21), Virtual Event, Canada, July 11–15, 2021: 275-284. (CCF A)
[9]. Xing Chen, Dongcui Diao, Hechang Chen, Hengshuai Yao, Haiyin Piao, Zhixiao Sun, Zhiwei Yang, Randy Goebel, Bei Jiang, Yi Chang. The Sufficiency of Off-policyness and Soft Clipping: PPO is Still Insufficient According to an Off-policy Measure. In Proceedings of the 37th International Conference on the Association for the Advancement of Artificial Intelligence (AAAI’23), 2023, Feb. 07-14, Washington D.C., USA, 37, pp: 7078-7086. (CCF A)
[10]. Zhiwei Yang, Hechang Chen, Jiawei Zhang, Jing Ma, Yi Chang. Attention-based Multi-level Feature Fusion for Named Entity Recognition. In Proceedings of the 29th International Joint Conference on Artificial Intelligence (IJCAI’20), Virtual Event, Japan, January 7-15, 2021: 3594-3600. (CCF A)
[11]. Zhiwei Yang, Jing Ma, Hechang Chen, Jiawei Zhang, Yi Chang. Context-aware Attentive Multi-level Feature Fusion for Named Entity Recognition. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022, 35(1): 973-984. (中科院1区)
[12]. Zhaogeng Liu, Jielong Yang, Xionghu Zhong, Wenwu Wang, Hechang Chen, and Yi Chang. A Novel Composite Graph Neural Network. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2023. 1-15. (中科院1区)
[13]. Liu Zhaogeng, Ji Feng, Yang Jielong, Cao Xiaofeng, Zhang Muhan, Chen Hechang, Chang Yi. Refining Euclidean Obfuscatory Nodes Helps: A Joint-Space Graph Learning Method for Graph Neural Networks. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2024. (中科院1区)
[14]. Haiyin Piao, Shengqi Yang, Hechang Chen, Junnan Li, Jin Yu, Xuanqi Peng, Xin Yang, Zhen Yang, Zhixiao Sun, Yi Chang. Discovering Expert-Level Air Combat Knowledge via Deep Excitatory-Inhibitory Factorized Reinforcement Learning. ACM Transactions on Intelligent Systems and Technology (TIST), 2024.
[15]. Xueyan Liu, Bo Yang, Hechang Chen, Katarzyna Musial, Hongxu Chen, Yang Li, Wanli Zuo. A Scalable Redefined Stochastic Blockmodel. ACM Transactions on Knowledge Discovery from Data (TKDD), 2021, 15(3): 46:1-46:28.
[16]. Xinqi Du, Hechang Chen, Che Wang, Yongheng Xing, Jielong Yang, Philip S. Yu, Yi Chang, Lifang He. Robust Multi-agent Reinforcement Learning via Bayesian Distributional Value Estimation. Pattern Recognition, available online 28 August 2023, 109917. (中科院1区)
[17]. Xinqi Du, Hechang Chen, Bo Yang, Cheng Long, and Songwei Zhao. HRL4EC: Hierarchical Reinforcement Learning for Multi-mode Epidemic Control. Information Sciences 640 (2023): 119065 - 119065. (中科院1区)
[18]. Zhiwei Yang, Jing M, Kang Yang, Huiru Lin, Hechang Chen, Ruichao Yang, Yi Chang. CoTea: Collaborative Teaching for Low-resource Named Entity Recognition with A Divide-and-conquer Strategy. Information Processing and Management, Volume 61, Issue 3, May 2024, 103657. (中科院1区)
[19]. Xinqi Du, Hechang Chen, Yongheng Xing, Philip S. Yu, Lifang He. A Contrastive-Enhanced Ensemble Framework for Efficient Multi-Agent Reinforcement Learning. Expert Systems with Applications, 2024. (中科院1区)
[20]. Bo Yang, Hongbin Pei, Hechang Chen, Jiming Liu, Shang Xia. Characterizing and Discovering Spatiotemporal Social Contact Patterns for Healthcare. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2017, 39(8): 1532-1546. (CCF A)
