改进的 KNN-SMOreg 算法及在铀矿床典型蚀变矿物赤铁矿含量预测中的应用 吴佳, 蔡之华, 高哲超 应用基础与工程科学学报 19 (5), 842-851, 2011 | | 2011 |
基于实例克隆的 ICSMOreg 算法及在铀矿床蚀变矿物水云母中的物谱建模研究 吴佳, 蔡之华, 高哲超, 余超 光谱学与光谱分析 31 (6), 1678-1682, 2011 | 1 | 2011 |
自适应差分演化算法在图像监督分类中的应用 吴佳, 蔡之华, 金晓文 武汉大学学报 (信息科学版) 38 (1), 23-26, 2013 | | 2013 |
A brain network inspired algorithm: pre-trained extreme learning machine Y Zhang, J Wu, Z Cai, S Jiang Neural Information Processing: 24th International Conference, ICONIP 2017 …, 2017 | 3 | 2017 |
A combined classification algorithm based on C4. 5 and NB L Jiang, C Li, J Wu, J Zhu Advances in Computation and Intelligence: Third International Symposium …, 2008 | 8 | 2008 |
A combined method based on visual and communication for simulative agent localization J Wu, Z Cai, H Zheng, X Liu, P Chen JDCTA (International Journal of Digital Content Technology and its …, 2012 | 2 | 2012 |
A comprehensive survey of graph-level learning Z Yang, G Zhang, J Wu, J Yang, QZ Sheng, S Xue, C Zhou, C Aggarwal, ... arXiv preprint arXiv:2301.05860, 2023 | 11 | 2023 |
A comprehensive survey of the key technologies and challenges surrounding vehicular ad hoc networks Z Xia, J Wu, L Wu, Y Chen, J Yang, PS Yu ACM Transactions on Intelligent Systems and Technology (TIST) 12 (4), 1-30, 2021 | 53 | 2021 |
A comprehensive survey on automatic knowledge graph construction L Zhong, J Wu, Q Li, H Peng, X Wu ACM Computing Surveys 56 (4), 1-62, 2023 | 32 | 2023 |
A Comprehensive Survey on Collaborative Data-access Enablers in the IIoT D Sun, J Hu, H Wu, J Wu, J Yang, QZ Sheng, S Dustdar ACM Computing Surveys 56 (2), 1-37, 2023 | 2 | 2023 |
A comprehensive survey on community detection with deep learning X Su, S Xue, F Liu, J Wu, J Yang, C Zhou, W Hu, C Paris, S Nepal, D Jin, ... IEEE Transactions on Neural Networks and Learning Systems, 2022 | 336 | 2022 |
A comprehensive survey on deep clustering: Taxonomy, challenges, and future directions S Zhou, H Xu, Z Zheng, J Chen, J Bu, J Wu, X Wang, W Zhu, M Ester arXiv preprint arXiv:2206.07579, 2022 | 71 | 2022 |
A comprehensive survey on graph anomaly detection with deep learning X Ma, J Wu, S Xue, J Yang, C Zhou, QZ Sheng, H Xiong, L Akoglu IEEE Transactions on Knowledge and Data Engineering 35 (12), 12012-12038, 2021 | 493 | 2021 |
A comprehensive survey on graph summarization with graph neural networks N Shabani, J Wu, A Beheshti, QZ Sheng, J Foo, V Haghighi, A Hanif, ... IEEE Transactions on Artificial Intelligence, 2024 | 4 | 2024 |
A comprehensive survey on pretrained foundation models: A history from bert to chatgpt C Zhou, Q Li, C Li, J Yu, Y Liu, G Wang, K Zhang, C Ji, Q Yan, L He, ... arXiv preprint arXiv:2302.09419, 2023 | 369 | 2023 |
A Comprehensive Survey on Schema-based Event Extraction with Deep Learning Q Li, H Peng, J Li, Y Hei, R Sun, J Sheng, S Guo, L Wang, J Wu, ... arXiv preprint arXiv:2107.02126 14, 1, 2021 | 7 | 2021 |
A correlation-based feature weighting filter for naive Bayes L Jiang, L Zhang, C Li, J Wu IEEE transactions on knowledge and data engineering 31 (2), 201-213, 2018 | 232 | 2018 |
A data stream cleaning system using edge intelligence for smart city industrial environments D Sun, S Xue, H Wu, J Wu IEEE Transactions on Industrial Informatics 18 (2), 1165-1174, 2021 | 19 | 2021 |
A Decomposition Dynamic graph convolutional recurrent network for traffic forecasting W Weng, J Fan, H Wu, Y Hu, H Tian, F Zhu, J Wu Pattern Recognition 142, 109670, 2023 | 34 | 2023 |
A deep framework for cross-domain and cross-system recommendations F Zhu, Y Wang, C Chen, G Liu, M Orgun, J Wu arXiv preprint arXiv:2009.06215, 2020 | 136 | 2020 |