[1] Jiye Liang, Zijin Du, Jianqing Liang, Kaixuan Yao, Feilong Cao. Long and short-range dependency graph structure learning framework on point cloud. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023, 45(12): 14975-14989.

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

[3] Liang Bai, Jiye Liang, K-relations-based consensus clustering with entropy-norm regularizers, IEEE Transactions on Neural Networks and Learning Systems, 2023, DOI: 10.1109/TNNLS.2023.3307158.

[4] Liang Bai, Jiye Liang, Yuxiao Zhao, Self-constrained spectral clustering, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023, 45(4): 5126-5138.

[5] YechengGuo, Liang Bai, Xian Yang, Jiye Liang. Improving image contrastive clustering through self-Learning pairwise constraints. IEEE Transactions on Neural Networks and Learning Systems, 2023, DOI: 10.1109/TNNLS.2023.3329494.

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

[7] Liancheng He, Liang Bai, Xian Yang, Hangyuan Du, Jiye Liang. High-order graph attention network. Information Sciences, 2023, 630:222-234.

[8] Yujie Fu, Suge Wang, Xiaoli Li, Deyu Li, Yang Li, Jian Liao, JianxingZheng. Hierarchical neural network: Integrate divide-and-conquer and unified approach for argument unit recognition and classification. Information Sciences, 2023, 624: 796-810.

[9] Hang Xu, Shuai Ma, Wenjian Wang. An ordered feature recognition method based on ranking separability. Information Sciences, 2023, 648: 119518.

[10] HushengGuo, Haosen Xia, Hai Li, Wenjian Wang. Concept evolution detection based on noise reduction soft boundary. Information Sciences, 2023, 628: 391-408.

[11] Jing Yan, Wei Wei, XinyaoGuo, Chuangyin Dang, Jiye Liang. A bi-level metric learning framework via self-paced learning weighting. Pattern Recognition, 2023, 139: 109446.

[12] Hangyuan Du, Wenjian Wang, Liang Bai. Dual-channel embedding learning model for partially labelled attributed networks: A Mutual Information Perspective. Pattern Recognition, 2023, 142: 109644.

[13] YaqingGuo, Wenjian Wang. A robust adaptive linear regression method for severe noises. Knowledge and Information System, 2023, 65: 4613–4653.

[14] Wentao Cui, Liang Bai, Contrastive learning with the feature reconstruction amplifier, In Proceedings of the 37th AAAI Conference on Artificial Intelligence, 2023.

[15] ShaoruGuo, Chenhao Wang, Yubo Chen, Kang Liu, Ru Li, and Jun Zhao.EventOA: an event ontology alignment benchmark based on framenet and wikidata. In Findings of the Association for Computational Linguistics, 10038–10052, (ACL) 2023.

[16] Yujie Wang, Hu Zhang, Jiye Liang, Ru Li. Dynamic heterogeneous-graph reasoning with language models and knowledge representation learning for commonsense question answering. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 14048–14063, (ACL) 2023.

[17] Wei Wei, Lijun Zhang, Lin Li, Huizhong Song, Jiye Liang. Set-membership belief state-based reinforcement learning for POMDPs. Proceedings of the International Conference on Machine Learning, 2023, 36856-36867.

[18] Junbiao Cui, Jianqing Liang, Qin Yue, Jiye Liang. A general representation learning framework with generalization performance guarantees. Proceedings of the 40th International Conference on Machine Learning (ICML)2023.

[19] RuiliPu, Yang Li, Suge Wang, Deyu Li, JianxingZheng, Jian Liao. Enhancing event causality identification with event causal label and event pair interaction graph, ACL 2023, 10314–10322.

[20] 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.电子学报, 2023, 51(6):1458-1467.

[21] 郭虎升, 丛璐, 高淑花, 王文剑. 基于在线集成的概念漂移自适应分类方法.计算机研究与发展, 2023, 60(7):1592-1602.