1、新型深度学习模型与方法的研究,-2020.12,2018.01,周志华,应急管理项目,国家自然科学基金委员会,61751306，参与。 2、大数据分析的基础理论和技术方法,-2021.04,2018.05,周志华,国家重点研发计划“云计算与大数据”专项项目,科技部,2018YFB1004300，参与。 3、面向开放动态环境的机器学习,-2024.12,2020.01,周志华,创新群体项目,国家自然科学基金委员会,61921006，参与。 1、[AISTATS 2023] On the Consistency Rate of Decision Tree Learning Algorithms. Qin-Cheng Zheng, Shen-Huan Lyu, Shao-Qun Zhang, Yuan Jiang, and Zhi-Hua Zhou. In Proceedings of the 26th International Conference on Artificial Intelligence and Statistics, 2023.,CCF C类 2、[NeurIPS 2022 Oral] Depth is More Powerful than Width with Prediction Concatenation in Deep Forest. Shen-Huan Lyu, Yi-Xiao He, and Zhi-Hua Zhou. In: Advances in Neural Information Processing Systems 35, New Orleans, Louisiana, US, 2022.,CCF A类 3、[NN 2022] Improving Generalization of Neural Networks by Leveraging Margin Distribution. Shen-Huan Lyu, Lu Wang, and Zhi-Hua Zhou. Neural Networks, 151:48-60, 2022.,中科院1区 Top 4、[CJE 2022] A Region-based Analysis for the Feature Concatenation in Deep Forests. Shen-Huan Lyu, Yi-He Chen, and Zhi-Hua Zhou. Chinese Journal of Electronics, 2022.,国内顶级英文期刊 5、[JOS 2023] 基于交互表示的多标记深度森林方法. 吕沈欢, 陈一赫, 姜远. 软件学报, 2023.,国内顶级中文期刊 6、[ICDM 2021] Improving Deep Forest by Exploiting High-order Interactions. Yi-He Chen*, Shen-Huan Lyu*, and Yuan Jiang (* indicates equal contribution). In: Proceedings of the 21st IEEE International Conference on Data Mining, pp. 1030-1035, Auckland, NZ, 2021.,CCF B类 7、[NeurIPS 2019] A Refined Margin Distribution Analysis for Forest Representation Learning. Shen-Huan Lyu, Liang Yang, and Zhi-Hua Zhou. In: Advances in Neural Information Processing Systems 32, pp. 5531-5541, Vancouver, British Columbia, CA, 2019.,CCF A类