[1] Fuyuan Cao, Xuechun Jing*, Kui Yu, Jiye Liang. FWCEC: An Enhanced Feature Weighting Method via Causal Effect for Clustering[J]. IEEE Transactions on Knowledge and Data Engineering, 2025, 37(2): 685-697

[2] Xuecheng Ning, Yujie Wang, Kui Yu, Jiali Miao, Fuyuan Cao, Jiye Liang. Summary Graph Induced Invariant Learning for Generalizable Graph Learning[J]. IEEE Transactions on Knowledge and Data Engineering, 2025

[3] Kui Yu, Chen Rong, Hao Wang, Fuyuan Cao, Jiye Liang. Federated local causal structure learning[J]. Science China Information Sciences, 2025, 68(3): 132105

[4] Xuechun Jing, Fuyuan Cao*, Kui Yu, Jiye Liang. CM-CaFE: A Clustering Method with Causality-based Feature Embedding[J]. ACM Transactions on Knowledge Discovery from Data, 2025

[5] Qingqiang Chen, Fuyuan Cao*, Ying Xing, Jiye Liang. An Efficient Bayes Error Rate Estimation Method, Machine Learning, 2025

[6] Yongsheng Zhao, Kui Yu, Guodu Xiang, Xianjie Guo, Fuyuan Cao. FedECE: Federated Estimation of Causal Effect Based on Causal Graphical Modelling[J]. IEEE Transactions on Artificial Intelligence, 2025

[7] Fuyuan Cao, Qingqiang Chen*, Ying Xing, Jiye Liang. Efficient classification by removing bayesian confusing samples[J]. IEEE Transactions on Knowledge and Data Engineering, 2024, 36(3): 1084-1098

[8] Fuyuan Cao, Yunxia Wang*, Kui Yu, Jiye Liang. Causal Discovery from Unknown Interventional Datasets over Overlapping Variable Sets[J]. IEEE Transactions on Knowledge and Data Engineering, 2024, 36(12): 7725-7742

[9] Shujing Yang, Fuyuan Cao*, Kui Yu, Jiye Liang. Learning causal chain graph structure via alternate learning and double pruning[J]. IEEE Transactions on Big Data, 2024, 10(4): 442-456

[10] Jing Liu, Fuyuan Cao*, Xuechun Jing, Jiye Liang. Deep multi-view graph clustering network with weighting mechanism and collaborative training[J]. Expert Systems with Applications, 2024, 236: 121298

[11] Shujing Yang, Fuyuan Cao*. Block Domain Knowledge-Driven Learning of Chain Graphs Structure[J]. Journal of Artificial Intelligence Research, 2024, 80: 209-242

[12] Qingqiang Chen, Gaoxia Jiang, Fuyuan Cao, Changqian Men, Wenjian Wang*. A general elevating framework for label noise filters[J]. Pattern Recognition, 2024, 147: 110072

[13] Yujie Wang, Kui Yu*, Guodu Xiang, Fuyuan Cao, Jiye Liang. Discovering causally invariant features for out-of-distribution generalization[J]. Pattern Recognition, 2024, 150: 110338

[14] Guodu Xiang, Hao Wang, Kui Yu*, Xianjie Guo, Fuyuan Cao, Yukun Song. Bootstrap-Based Layerwise Refining for Causal Structure Learning[J]. IEEE Transactions on Artificial Intelligence, 2024, 5(6): 2708-2722

[15] Xianjie Guo, Kui Yu*, Lin Liu, Fuyuan Cao, Jiuyong Li. Causal feature selection with dual correction[J]. IEEE Transactions on Neural Networks and Learning Systems, 2024, 35(1): 938-951

[16] Qingqiang Chen, Fuyuan Cao*, Ying Xing, Jiye Liang*. Evaluating classification model against Bayes error rate[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023, 45(8): 9639-9653

[17] Shuai Yang, Kui Yu, Fuyuan Cao, Lin Liu, Hao Wang, Jiuyong Li. Yang S, Yu K, Cao F, et al. Learning causal representations for robust domain adaptation[J]. IEEE Transactions on Knowledge and Data Engineering, 2023, 35(3): 2750-2764

[18] Yunxia Wang, Fuyuan Cao*, Kui Yu, Jiye Liang. Local causal discovery in multiple manipulated datasets[J]. IEEE Transactions on Neural Networks and Learning Systems, 2023, 34(10): 7235-7247

[19] Yilu Liu, Fuyuan Cao*. A relative labeling importance estimation algorithm based on global-local label correlations for multi-label learning[J]. Applied Intelligence, 2023, 53(5): 4940-4958

[20] Jianli Huang, Xianjie Guo, Kui Yu, Fuyuan Cao, Jiye Liang. Towards privacy-aware causal structure learning in federated setting[J]. IEEE Transactions on Big Data, 2023, 9(6): 1525-1535

[21] Qingqiang Chen, Fuyuan Cao*, Ying Xing, Jiye Liang. Instance selection: A Bayesian decision theory perspective[C]//Proceedings of the AAAI Conference on Artificial Intelligence, 2022, 36(6): 6287-6294

[22] Yunxia Wang, Fuyuan Cao*, Kui Yu, Jiye Liang. Efficient causal structure learning from multiple interventional datasets with unknown targets[C]//Proceedings of the AAAI Conference on Artificial Intelligence, 2022, 36(8): 8584-8593

[23] Jiye Liang*, Xiaolin Liu, Liang Bai, Fuyuan Cao, Dianhui Wang. Incomplete multi-view clustering via local and global co-regularization[J]. Science China Information Sciences, 2022, 65(5): 152105

[24] Liqin Yu, Fuyuan Cao*. Weighted matrix-object data clustering guided by matrix-object distributions[J]. Engineering Applications of Artificial Intelligence, 2022, 109: 104612

[25] Jing Liu, Fuyuan Cao*, Jiye Liang. Centroids-guided deep multi-view K-means clustering[J]. Information Sciences, 2022, 609: 876-896

[26] Xianjie Guo, Kui Yu*, Fuyuan Cao, Pei-Pei Li, Hao Wang. Error-aware Markov blanket learning for causal feature selection[J]. Information Sciences, 2022, 589: 849-877

[27] Shuai Yang, Hao Wang, Kui Yu*, Fuyuan Cao, Xindong Wu. Towards efficient local causal structure learning[J]. IEEE Transactions on Big Data, 2022, 8(6): 1592-1609

[28] Shuai Yang, Kui Yu*, Fuyuan Cao, Hao Wang, Xindong Wu. Dual-representation-based autoencoder for domain adaptation[J]. IEEE Transactions on Cybernetics, 2022, 52(8): 7464-7477

[29] Fuyuan Cao*, Xiaolin Wu, Liqin Yu, Jiye Liang. An outlier detection algorithm for categorical matrix-object data. Applied Soft Computing, 2021, 104: 107182

[30] Liqin Yu, Fuyuan Cao*, Xiao-Zhi Gao, Jing Liu, Jiye Liang. k-Mnv-Rep: A k-type clustering algorithm for matrix-object data[J]. Information Sciences, 2021, 542: 40-57

[31] Liang Bai, Jiye Liang*, Fuyuan Cao. Semi-supervised clustering with constraints of different types from multiple information sources[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021, 43(9): 3247-3258

[32] Jing Liu, Fuyuan Cao, Xiao-Zhi Gao, Liqin Yu, Jiye Liang*. A cluster-weighted kernel K-means method for multi-view clustering[C]//Proceedings of the AAAI Conference on Artificial Intelligence, 2020: 4860-4867

[33] Liqin Yu, Fuyuan Cao*, Xingwang Zhao, Xiaodan Yang, Jiye Liang. Combining attribute content and label information for categorical data ensemble clustering[J]. Applied Mathematics and Computation, 2020, 381: 125280

[34] Liang Bai, Jiye Liang*, Fuyuan Cao. A multiple k-means clustering ensemble algorithm to find nonlinearly separable clusters[J]. Information Fusion, 2020, 61: 36-47

[35] Hongju Yang*, Yao Li, Xuefeng Yan, Fuyuan Cao. ContourGAN: Image contour detection with generative adversarial network[J]. Knowledge-Based Systems, 2019, 164: 21-28

[36] Fuyuan Cao, Joshua Zhexue Huang*, Jiye Liang, etc. An algorithm for clustering categorical data with set-valued features[J]. IEEE Transactions on Neural Networks and Learning Systems, 2018, 29(10): 4593-4606

[37] Xingwang Zhao, Fuyuan Cao, Jiye Liang*. A sequential ensemble clusterings generation algorithm for mixed data[J]. Applied Mathematics and Computation, 2018, 335: 264-277

[38] Qingqiong Cai, Fuyuan Cao, Tao Li*, Hua Wang. On distances in vertex-weighted trees[J]. Applied Mathematics and Computation, 2018, 333: 435-442

[39] Yinfeng Meng, Jiye Liang*, Fuyuan Cao, Yijun He. A new distance with derivative information for functional k-means clustering algorithm[J]. Information Sciences, 2018: 463-464. : 166-185

[40] Fuyuan Cao*, Joshua Zhexue Huang, Jiye Liang. A fuzzy SV-k-modes algorithm for clustering categorical data with set-valued attributes[J]. Applied Mathematics and Computation, 2017, 295: 1-15

[41] Fuyuan Cao, Liqin Yu, Joshua Zhexue Huang, Jiye Liang*. k-mw-modes: An algorithm for clustering categorical matrix-object data[J]. Applied Soft Computing, 2017, 57: 605-614

[42] Fuyuan Cao, Joshua Zhexue Huang*, Jiye Liang. Trend analysis of categorical data streams with a concept change method[J]. Information Sciences, 2014, 276: 160-173

[43] Xingwang Zhao*, Jiye Liang, Fuyuan Cao. A simple and effective outlier detection algorithm for categorical data[J]. International Journal of Machine Learning and Cybernetics, 2014, 5(3): 469-477

[44] Fuyuan Cao, Jiye Liang*, Deyu Li, Xingwang Zhao. A weighting K-Modes algorithm for subspace clustering of categorical data[J]. Neurocomputing, 2013, 108: 23-30

[45] Fuyuan Cao, Joshua Zhexue Huang*, A concept-drifting detection algorithm for categorical evolving data[C]//PAKDD, 2013: 492-503

[46] Liang Bai, Jiye Liang, Chuangyin Dang, Fuyuan Cao. The impact of cluster representatives on the convergence of the K-Modes type clustering[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2013, 35(6): 1509-1522

[47] Liang Bai, Jiye Liang*, Chuangyin Dang, Fuyuan Cao. A novel fuzzy clustering algorithm with between-cluster information for categorical data[J]. Fuzzy Sets and Systems, 2013, 215(3): 55-73

[48] Ming Gao, Fuyuan Cao, Joshua Zhexue Huang. A cross cluster-based collaborative filtering method for recommendation[C]//Proceeding of the IEEE International Conference on Information and Automation, 447-452, 2013

[49] Fuyuan Cao, Jiye Liang*, Deyu Li, Liang Bai, Chuangyin Dang. A dissimilarity measure for the K-Modes clustering algorithm[J]. Knowledge-Based Systems, 2012, 26(1): 120-127

[50] Jiye Liang*, Liang Bai, Chuangyin Dang, Fuyuan Cao. The K-Means type algorithms versus imbalanced data distributions[J]. IEEE Transactions on Fuzzy Systems, 2012, 20(4): 728-745

[51] Jiye Liang*, Xingwang Zhao, Deyu Li, Fuyuan Cao, Chuangyin Dang. Determining the number of clusters using information entropy for mixed data[J]. Pattern Recognition, 2012, 45(6): 2251-2265

[52] Liang Bai, Jiye Liang*, Chuangyin Dang, Fuyuan Cao. A cluster centers initialization method for clustering categorical data[J]. Expert Systems with Applications, 2012, 39(9): 8022-8029

[53] Fuyuan Cao, Jiye Liang*. A data labeling method for clustering categorical data[J]. Expert Systems with Applications, 2011, 38(3): 2381-2385

[54] Liang Bai, Jiye Liang*, Chuangyin Dang, Fuyuan Cao. A novel attribute weighting algorithm for clustering high-dimensional categorical data[J]. Pattern Recognition, 2011, 44(12): 2843-2861

[55] Fuyuan Cao, Jiye Liang*, Liang Bai, Xingwang Zhao, Chuangyin Dang. A framework for clustering categorical time-evolving data[J]. IEEE Transactions on Fuzzy Systems, 2010, 18(5): 872-882

[56] Fuyuan Cao, Jiye Liang*, Liang Bai. A new initialization method for categorical data clustering[J]. Expert Systems with Applications, 2009, 36(7): 10223-10228

[57] Fuyuan Cao, Jiye Liang*, Guang Jiang. An initialization method for the K-Means algorithm using neighborhood model[J]. Computers and Mathematics with Applications, 2009, 58(3): 474-483

[58] 曹付元*, 陈晓惠. 共享和特定表示的多视图属性图聚类[J]. 软件学报, 2025, 36(3): 1254-1267

[59] 曹付元*, 杨淑晶, 王雲霞, 俞奎. 基于约束的局部-全局 LWF 链图结构学习算法[J]. 电子学报, 2023, 51(6): 1458-1467

[60] 杨帅, 王浩, 俞奎, 曹付元. 基于实例加权和双分类器的稳定学习算法[J]. 软件学报, 2023, 34(7): 3206-3225

[61] 李顺勇*, 张苗苗, 曹付元. 基于分类型矩阵对象数据的MD fuzzy k-modes聚类算法[J]. 计算机研究与发展, 2019, 56(6): 1325-1337

[62] 梁吉业*, 乔洁, 曹付元, 刘晓琳. 面向短文本分析的分布式表示模型[J]. 计算机研究与发展, 2018, 55(8): 1631-1640

[63] 梁吉业*, 白亮, 曹付元. 基于新的距离度量的K-Modes聚类算法[J]. 计算机研究与发展, 2010, 47(10): 1749-1755

[1] 复杂多模态数据的聚类分析及云平台构建. 国家自然科学基金区域联合基金重点项目, 2025.01-2028.12, 主持人

[2] 因果表征的聚类算法研究. 国家自然科学基金面上项目, 2024.01-2027.12, 主持人

[3] 煤矿安全全时空多元感知技术与智能综合管控系统研究与应用, 太原市“双百攻关行动”关键核心技术攻关“揭榜挂帅”项目(课题), 2024.01-2026.12, 主持人

[4] 机器学习与因果推理. 山西省科技创新人才团队, 2022.05-2025.05, 主持人

[5] 山西省矿山智能感知技术创新中心. 山西省技术创新中心, 2022.01-2023.12, 主持人

[6] 广域数联网系统关键技术研究. 山西省科技重大专项计划“揭榜挂帅”项目(课题), 2022.01-2023.12, 主持人

[7] 面向广义多视图数据的聚类算法研究. 国家自然科学基金面上项目, 2020.01-2023.12, 主持人

[8] 面向中医电子病历大数据分析及示范应用. 山西省重点研发计划项目, 2018.10-2021.12, 主持人

[9] 大数据分割与融合方法研究. 山西省留学择优资助项目, 2017.01-2019.12, 主持人

[10] 面向关联关系数据的概念学习方法研究. 国家自然科学基金面上项目, 2016.01-2019.12, 主持人

[11] 面向跨领域数据的概念融合方法研究. 山西省留学基金项目, 2016.01-2018.12, 主持人

[12] 面向分类型块数据的聚类算法研究. 山西省自然科学基金项目, 2015.01-2017.12, 主持人

[13] 面向块数据的用户行为模式聚类算法研究. 中国博士后科学基金面上项目(一等资助), 2012.03-2013.12, 主持人

[14] 面向符号属性数据的聚类算法研究. 山西省自然科学青年基金项目, 2010.01-2012.12, 主持人

[15] 基于软计算的数据挖掘技术研究与实现. 山西高校科技研究开发项目, 2007.01-2009.12, 主持人

[16] 面向企业的智能数据分析平台. 太原市科技局项目, 2007.04. -2008.03, 主持人