最终学位：博士
导师类型：
电子邮箱：cjb@sxu.edu.cn
联系电话：0351-7010566
研究方向：机器学习
崔军彪，博士。2016年毕业于山西大学计算机与信息技术学院，获学士学位，2024年毕业于山西大学计算机与信息技术学院，获博士学位。研究兴趣主要包括机器学习与数据挖掘，重点围绕弱监督学习、开放环境分类、数据降维等问题开展学术研究。目前已在人工智能与数据挖掘领域国际顶级学术期刊IEEE Transactions on Knowledge and Data Engineering、Machine Learning、Pattern Recognition、Knowledge-Based Systems以及国际顶级学术会议Annual Conference on Neural Information Processing Systems (NeurIPS)、International Conference on Machine Learning (ICML)、ACM Knowledge Discovery and Data Mining (KDD)等上发表论文10余篇。
[1] Junbiao Cui, Jianqing Liang, Qin Yue, Jiye Liang. A general representation learning framework with generalization performance guarantees[C]. International Conference on Machine Learning, 2023, 6522-6544.
[2] Junbiao Cui, Jiye Liang, Fuzzy learning machine[C]. Advances in Neural Information Processing Systems. 2022, 36693-36705.
[3] Jiye Liang, Junbiao Cui, Jie Wang, Wei Wei. Graph-based semi-supervised learning via improving the quality of the graph dynamically[J]. Machine Learning, 2021, 110: 1345-1388.
[4] Wei Wei, Qin Yue, Kai Feng, Junbiao Cui, Jiye Liang. Unsupervised dimensionality reduction based on fusing multiple clustering results[J]. IEEE Transactions on Knowledge and Data Engineering, 2023, 35(3): 3211-3223.
[5] Qin Yue, Jiye Liang, Junbiao Cui, Liang Bai. Dual bidirectional graph convolutional networks for zero-shot node classification[C]. ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2022, 2408-2417.
[6] Qin Yue, Junbiao Cui, Liang Bai, Jianqing Liang, Jiye Liang. A zero-shot learning boosting framework via concept-constrained clustering[J]. Pattern Recognition, 2024, 145: 109937.
[7] Wei Wei, Junbiao Cui, Jiye Liang, Junhong Wang. Fuzzy rough approximations for set-valued data[J]. Information Sciences, 2016, 360: 181-201.
[8] Jie Wang, Jianqing Liang, Junbiao Cui, Jiye Liang. Semi-supervised learning with mixed-order graph convolutional networks[J]. Information Sciences, 2021, 573: 171-181.
[9] Wei Wei, Xiaoying Wu, Jiye Liang, Junbiao Cui, Yijun Sun. Discernibility matrix based incremental attribute reduction for dynamic data[J]. Knowledge-Based Systems, 2018, 140: 142-157.
[1] 科技创新2030-“新一代人工智能”重大项目. 认知计算基础理论与方法研究(No.2020AAA0106100), 2020.11-2024.10. 参与.
[2] 国家自然科学基金(联合基金)重点项目. 网络大数据分析挖掘的理论与方法(No.U21A20473), 2022.01-2025.12. 参与.
[3] 国家自然科学基金面上项目. 基于多粒度的半监督学习方法(No.61876103), 2019.01-2022.12. 参与.