科研成果 |
[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, IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(4): 4051–4070 (2023). <br> [2] Ran Wang, Shuyue Chen and Yu Yu. Extending version space theory to multi-label active learning with imbalanced data, Pattern Recognition, 142: 109690 (2023). <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] Ran Wang, Sam Kwong, Xu Wang*, and Yuheng Jia. Active k-labelsets ensemble for multi-label classification, Pattern Recognition, 109: 107583 (2021). <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 Transactions on 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). |
科研项目 |
国家自然科学基金 面上项目 62176160,2022–2025,58万,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> 广东省自然科学基金 杰出青年项目 2024B1515020109,2024–2028,100万,代价敏感下的深度网络对抗鲁棒性研究与应用 (主持)<br> 广东省自然科学基金 面上项目 2022A1515010791,2022–2024,10万,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 20200804193857002,2021–2022,14万,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61772344,2018–2021,62万,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 61811530324,2018–2020,10万,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 61732011,2018–2022,285万,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 61402460,2015–2017,24万,基于分治融合与主动学习的极速学习机方法研究 (主持) |