| 科研成果 |
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[1] Farhad Pourpanah, Moloud Abdar, Yuxuan Luo, Xinlei Zhou, Ran Wang*(通讯), Chee Peng Lim, Xi- Zhao Wang, and Q. M. Jonathan Wu. A Review of Generalized Zero-Shot Learning Methods, in press, IEEE Transactions on Pattern Analysis and Machine Intelligence, DOI: 10.1109/TPAMI.2022.3191696. <br>[2] Hong Zhu, Xizhao Wang*, and Ran Wang*(通讯). Fuzzy monotonic k-nearest neighbor versus monotonic fuzzy k-nearest neighbor, IEEE Transactions on Fuzzy Systems, 30(9): 3501–3513 (2022). <br>[3] Ran Wang*(通讯) and Zichao Zhang. Set theory based operator design in evolutionary algorithms for solving knapsack problems. IEEE Transactions on Evolutionary Computation, 25(6): 1133–1147 (2021).<br>[4] Xi-Zhao Wang, Tianlun Zhang, and Ran Wang*(通讯). Noniterative deep learning: Incorporating restricted boltzmann machine into multilayer random weight neural networks. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 49(7): 1299—1308 (2019). <br>[5] Ran Wang*(通讯), Chi-Yin Chow, Yan Lyu, Victor C. S. Lee, Sam Kwong, Yanhua Li, and JiaZeng. TaxiRec: Recommending road clusters to taxi drivers using ranking-based extreme learning machines. IEEE Transactions on Knowledge and Data Engineering, 30(3): 585—598 (2018). <br>[6] Xi-Zhao Wang, Ran Wang*(通讯), and Chen Xu. Discovering the relationship between generalization and uncertainty by incorporating complexity of classification. IEEE Transaction son Cybernetics, 48(2): 703—715 (2018). <br>[7] Ran Wang, Xi-Zhao Wang*, Sam Kwong, and Chen Xu. Incorporating diversity and informativeness in multiple-instance active learning. IEEE Transactions on Fuzzy Systems, 25(6): 1460—1475 (2017). <br>[8] Ran Wang, Chi-Yin Chow, and Sam Kwong*. Ambiguity based multiclass active learning. IEEE Transactions on Fuzzy Systems, 24(1): 242—248 (2016). <br>[9] Ran Wang, Sam Kwong*, Xi-Zhao Wang, and Qingshan Jiang. Segment based decision tree induction with continuous valued attributes. IEEE Transactions on Cybernetics, 45(7):1262–1275 (2015). <br>[10] Ran Wang, Degang Chen, and Sam Kwong*. Fuzzy rough set based active learning. IEEE Transactions on Fuzzy Systems, 22(6): 1699–1704 (2014).<br><br></p> |
科研项目 |
国家自然科学基金面上项目62176160，2022.01–2025.12，58万，基于不确定性建模的深度网络对抗鲁棒性研究与应用 (主持)<br>广东省基础与应用基础研究基金面上项目2022A1515010791，2022.01–2024.12，10万，深度学习中的不确定性分析、建模与应用 (主持)<br>深圳市高等院校稳定支持计划面上项目20200804193857002，2021.01–2022.12，14万，多标记学习中的不确定性理论与建模 (主持)<br>国家自然科学基金面上项目61772344，2018.01–2021.12，62万，多标记问题的不确定性分析与主动学习方法研究 (主持)<br>国家自然科学基金国际(地区)合作与交流项目61811530324，2018.04–2020.03，10万，多标记主动学习的关键问题：多目标优化、不确定性建模与多准则决策 (主持) <br>国家自然科学基金重点项目61732011，2018.01–2022.12，285万，面向大数据机器学习的不确定性建模理论与方法 (参与)<br>国家自然科学基金青年科学基金项目61402460，2015.01–2017.12，24万，基于分治融合与主动学习的极速学习机方法研究 (主持)<br> |
