百晓学者学者目录

梁吉业

山西大学计算机与信息技术学院

个人简介

梁吉业，山西大学计算机与信息技术学院教授、博士生导师，现任山西大学学术委员会主任、计算智能与中文信息处理教育部重点实验室主任，研究方向包括数据挖掘与机器学习、大数据分析技术、人工智能；在多粒度数据建模与图数据挖掘领域开展工作，主持科技创新2030—“新一代人工智能”重大项目及多项国家自然科学基金项目。

精选作品

期刊论文

  1. Zhihao Guo, Peng Song, Chenjiao Feng, Kaixuan Yao, Jiye Liang (2026). Causal inference for alleviating confounding bias in multi-criteria rating recommendation. Information Processing & Management, Vol. 63, No. 1.DOI
  2. 邱佳悦，叶海良，梁吉业，吕科，曹飞龙（2026）. 基于超图卷积的几何点云补全网络. 《计算机研究与发展》.
  3. 魏巍，宋慧忠，李琳，张利军，马亿，郝建业，梁吉业（2026）. 基于互信息引导信息聚合的多智能体强化学习方法. 《计算机学报》.
  4. 高小方，贾宗翰，梁吉业（2026）. 基于趋势一致性学习的对比聚类算法. 《智能系统学报》.
  5. Honghong Cheng, Yuhua Qian, Xinyan Liang, Jiye Liang, Qingfu Zhang (2026). Mining Association Patterns From Neighborhood Insight. IEEE Transactions on Pattern Analysis and Machine Intelligence.DOI
  6. Zeyu Wang, Feng Wang, Jiye Liang, Liang Bai (2026). Attribute evidence decomposition for generalized zero-shot learning. Information Sciences.DOI
  7. Jiye Liang, Haoyu Wang, Chenghao Fang, Kaixuan Yao (2026). Rethinking Multi-Modal Point Cloud Completion: Query-Aware Gating Attention and Gramian Volume Alignment. International Joint Conference on Artificial Intelligence.DOI
  8. Jiao Zhao, Junbiao Cui, Bin Zheng, Jiye Liang (2026). Domain generalization via decoupling class and domain discriminability: A sample perspective. Knowledge-Based Systems.DOI
  9. Yue Wang, Kui Yu, X Wang, Fuyuan Cao, Jiye Liang (2026). Invariant Subgraph Learning via Effective Environment Subgraph Augmentation for Generalizable Graph Neural Network. IEEE Transactions on Big Data.DOI
  10. Xi Wang, Liang Bai, Xian Yang, Jiye Liang (2026). Expanding Domain Generalization Theory: Error Bound Beyond Convex Combination Assumption. Machine Learning.DOI
  11. Yuxing Guo, Jianqing Liang, Kaixuan Yao, Zhihao Guo, Jiye Liang (2026). Graph Adversarial Defense via Hilbert-Schmidt Independence Criterion against Influence Maximization Attacks. ACM Web Conference (WWW).DOI
  12. Yue Fan, Hu Zhang, Ru Li, Guangjun Zhang, Yujie Wang, Hongye Tan, Yuanlong Wang, Xiaoli Li, Jiye Liang (2026). SRCR: Faithful structured reasoning with curriculum reinforcement learning for explainable question answering. Information Processing & Management.DOI
  13. Yu Bai, Liang Bai, Xian Feng Yang, Jiye Liang (2026). Graph-Enhanced Visual Prompting for Pre-Trained Models Adaptation in Medical Imaging Classification. IEEE Transactions on Medical Imaging.DOI
  14. Pengpeng Qiang, Hongye Tan, Hu Zhang, Xiaoli Li, Ru Li, Jiye Liang (2026). Mitigating Hallucinations in Large Vision-Language Models via Visual-Enhanced Contrastive Decoding. IEEE Transactions on Multimedia.DOI
  15. Yunxiao Zhao, Xu Hao, Zhiqiang Wang, Xiaoli Li, Jiye Liang, Ru Li (2026). Explaining Black-Box Language Models with Knowledge Probing Systems: A Post-hoc Explanation Perspective. Lecture notes in computer science.DOI
  16. Hailiang Ye, Jiayue Qiu, Feilong Cao, Jiye Liang, Ke Lü (2026). Geometry-Aware Point Cloud Completion via Sharpen-Hypergraph Convolution and Equivariance Operators. IEEE Transactions on Circuits and Systems for Video Technology.DOI
  17. Yujie Qin, Guoping Lin, Jiye Liang, Jianwei Lin, Yaojin Lin (2026). A Fuzzy Rough Set Framework for Interval-Valued Multilabel Feature Selection With Label Enhancement. IEEE Transactions on Fuzzy Systems.DOI
  18. Anhui Tan, Yu Wang, Weiping Ding, Jiye Liang, Witold Pedrycz (2026). Class-Specific Feature Learning and View Fusion for Multi-View Partial Multi-Label Learning. IEEE Transactions on Multimedia.DOI
  19. Juntao Yang, Kui Yu, Fuyuan Cao, Xiang Wang, Shuai Yang, Jiye Liang (2026). Gravitation and Causality Guided Multi-View Unsupervised Feature Selection. IEEE Transactions on Knowledge and Data Engineering.DOI
  20. Yuxin Fan, Junbiao Cui, Changhao Liu, Xingwang Zhao, Jiye Liang (2026). Debiased Textual Prompt Tuning for Enhancing Unknown Class Discovery. Lecture notes in computer science.DOI
  21. Shenao Yu, Fenglin Cen, Ji Hui Xu, Jiye Liang (2026). Heterogeneous Graph Condensation Via Joint-Granularity Gradient Matching. IEEE Transactions on Knowledge and Data Engineering.DOI
  22. 王锋，武文强，梁吉业（2025）. 面向开放世界的半监督特征选择算法. 《计算机学报》.
  23. 游秀，张红，梁吉业（2025）. 通信链路故障下高阶非匹配非线性MAS领导跟随一致性. 《自动化学报》.
  24. 徐祺津，叶海良，曹飞龙，梁吉业（2025）. 基于全局-局部先验和纹理细节关注的图像修复. 《模式识别与人工智能》.DOI
  25. Yunxiao Zhao, Zhiqiang Wang, Xingtong Yu, Xiaoli Li, Jiye Liang, Ru Li (2025). Learnable Game-Theoretic Policy Optimization for Data-Centric Self-Explanation Rationalization. IEEE Transactions on Knowledge and Data Engineering.DOI
  26. Feng Wang, Zeyu Wang, Jiye Liang (2025). Feature selection algorithm for dynamically evolving feature spaces. Neurocomputing.DOI
  27. Anhui Tan, Jianhang Xu, Weiping Ding, Jiye Liang, Witold Pedrycz (2025). Multi-View Partial Multi-Label Learning via Class Activation Specific Features Collaborative Learning. IEEE Transactions on Emerging Topics in Computing.DOI
  28. Zhichao Yan, Jiapu Wang, Jiaoyan Chen, Xiaoli Li, Jiye Liang, Ru Li, Jeff Z. Pan (2025). Atomic Fact Decomposition Helps Attributed Question Answering. IEEE Transactions on Knowledge and Data Engineering.DOI
  29. Zhikang Xu, Jiye Liang, Zhipeng Wei, Xiaodong Yue, Deyu Li (2025). Clinical knowledge enhanced medical image classification. Pattern Recognition.DOI
  30. Jiandong Shi, Ming Li, Lu Bai, Feilong Cao, Ke Lu, Jiye Liang (2025). MATCH: Modality-Calibrated Hypergraph Fusion Network for Conversational Emotion Recognition. International Joint Conference on Artificial Intelligence.DOI
  31. Chenghao Fang, Jianqing Liang, Jiye Liang, Hangkun Wang, Kaixuan Yao, Feilong Cao (2025). Multi-Modal Point Cloud Completion with Interleaved Attention Enhanced Transformer. International Joint Conference on Artificial Intelligence.DOI
  32. Zhiqiang Li, Jie Wang, Jianqing Liang, Junbiao Cui, Xingwang Zhao, Jiye Liang (2025). Uncertainty-guided Graph Contrastive Learning from a Unified Perspective. International Joint Conference on Artificial Intelligence.DOI
  33. Yuxin Fan, Junbiao Cui, Jiye Liang, Jianqing Liang (2025). Open-World Semi-Supervised Learning with Class Semantic Correlations. International Joint Conference on Artificial Intelligence.DOI
  34. Anhui Tan, Jianhang Xu, Wei-Zhi Wu, Weiping Ding, Jiye Liang (2025). Partial Multilabel Learning via Dynamic Fuzzy Aggregations of Multigranularity Features. IEEE Transactions on Fuzzy Systems.DOI
  35. Yujia Zhang, Lin Li, Wei Wei, Jianguo Wu, Jiye Liang (2025). Pseudo-distribution elite critics: Enhancing accuracy in reinforcement learning value estimation. Neural Networks.DOI
  36. Wei Wei, Jianguo Wu, Xinyao Guo, Jing Yan, Jiye Liang (2025). Self-Constrained Clustering Ensemble. IEEE Transactions on Pattern Analysis and Machine Intelligence.DOI
  37. Zhihao Guo, Peng Song, Chenjiao Feng, Kaixuan Yao, Jiye Liang (2025). Causal Inference for Multi-Criteria Rating Recommender Systems. ACM Transactions on Information Systems.DOI
  38. Zhihao Guo, Ting Han, Peng Song, Chenjiao Feng, Kaixuan Yao, Jiye Liang (2025). Hyperbolic Multi-Criteria Rating Recommendation. International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR).DOI
  39. Shujing Yang, Fuyuan Cao, Kui Yu, Jiye Liang (2025). Chain graphs structure learning given local background knowledge. International Journal of Approximate Reasoning.DOI
  40. Yuxin Fan, Junbiao Cui, Jiye Liang (2025). Learning Textual Prompts for Open-World Semi-Supervised Learning. IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings.DOI
  41. Tao Yan, Yuhua Qian, Jiangfeng Zhang, Jieting Wang, Jiye Liang (2025). SAS: A General Framework Induced by Sequence Association for Shape From Focus. IEEE Transactions on Pattern Analysis and Machine Intelligence.DOI
  42. Yu Bai, Liang Bai, Xian Feng Yang, Jiye Liang (2025). Label-Semantic-Based Prompt Tuning for Vision Transformer Adaptation in Medical Image Analysis. IEEE Transactions on Circuits and Systems for Video Technology.DOI
  43. Zhuomin Liang, Liang Bai, Xian Feng Yang, Jiye Liang (2025). Multi-Channel Disentangled Graph Neural Networks With Different Types of Self-Constraints. IEEE Transactions on Pattern Analysis and Machine Intelligence.DOI
  44. Anhui Tan, Yu Wang, Wei-Zhi Wu, Weiping Ding, Jiye Liang (2025). Multi-View Fusion Graph Attention Network for Multilabel Class Incremental Learning. Information Fusion.DOI
  45. Zijin Du, Jiye Liang, Kaixuan Yao, Feilong Cao (2025). TSI-GCN: Translation and scaling invariant GCN for 3D point cloud analysis. Pattern Recognition Letters.DOI
  46. Zihao Li, Xiaodong Yue, Jiye Liang, Jie Shi, Zhipeng Wei (2025). MU-OLTC: meta uncertainty calibration for open-set long-tailed classification. International Journal of Machine Learning and Cybernetics.DOI
  47. Jianqing Liang, Xinkai Wei, Min Chen, Zhiqiang Wang, Jiye Liang (2025). GNN-Transformer Cooperative Architecture for Trustworthy Graph Contrastive Learning. Proceedings of the AAAI Conference on Artificial Intelligence.DOI
  48. Qingqiang Chen, Fuyuan Cao, Ying Xing, Jiye Liang (2025). An efficient Bayes error rate estimation method. Machine Learning.DOI
  49. Da Wang, Lin Li, Wei Wei, Qixian Yu, Jianye Hao, Jiye Liang (2025). Improving Generalization in Offline Reinforcement Learning via Latent Distribution Representation Learning. Proceedings of the AAAI Conference on Artificial Intelligence.DOI
  50. Peiyao Wang, Liang Bai, Xian Feng Yang, Xi Wang, Jiye Liang (2025). Generalization Error Bounds for Graph Neural Networks in Unseen Domains. IEEE Transactions on Artificial Intelligence.DOI
  51. Da Wang, Wei Wei, Lin Li, Xin Wang, Jiye Liang (2025). Rethinking exploration–exploitation trade-off in reinforcement learning via cognitive consistency. Neural Networks.DOI
  52. Xuecheng Ning, Yujie Wang, Kui Yu, Jiali Miao, Fuyuan Cao, Jiye Liang (2025). Summary Graph Induced Invariant Learning for Generalizable Graph Learning. IEEE Transactions on Knowledge and Data Engineering.DOI
  53. Zhiqiang Wang, Baijing Hu, Kaixuan Yao, Jiye Liang (2025). Hawkes Point Process-enhanced Dynamic Graph Neural Network.DOI
  54. Xuechun Jing, Fuyuan Cao, Kui Yu, Jiye Liang (2025). CM-CaFE: A Clustering Method with Causality-based Feature Embedding. ACM Transactions on Knowledge Discovery from Data.DOI
  55. Hangyuan Du, Wenjian Wang, Weihong Zhang, Dengke Su, Liang Bai, Liang Bai, Jiye Liang (2025). Learning robust MLPs on graphs via cross-layer distillation from a causal perspective. Pattern Recognition.DOI
  56. Kui Yu, Rong Chen, Hao Wang, Fuyuan Cao, Jiye Liang (2025). Federated local causal structure learning. Science China Information Sciences.DOI
  57. Pengpeng Qiang, Hongye Tan, Xiaoli Li, Dian Wang, Ru Li, Xinyi Sun, Hu Zhang, Jiye Liang (2025). Enhancing few-shot KB-VQA with panoramic image captions guided by Large Language Models. Neurocomputing.DOI
  58. Huimin Yan, Xian Feng Yang, Liang Bai, Jiye Liang (2025). Local Alignment for Medical Vision-Language Pre-Training. IEEE Transactions on Image Processing.DOI
  59. Zhuomin Liang, Liang Bai, Xian Feng Yang, Jiye Liang (2025). Graph Contrastive Learning for Fusion of Graph Structure and Attribute Information. IEEE Transactions on Multimedia.DOI
  60. Huimin Yan, Xian Feng Yang, Liang Bai, Jiamin Li, Jiye Liang (2025). Multi-Grained Vision-and-Language Model for Medical Image and Text Alignment. IEEE Transactions on Multimedia.DOI
  61. Jun Wang, Fuyuan Cao, Zhixin Xue, Xingwang Zhao, Jiye Liang (2025). CMoB: Modality Valuation via Causal Effect for Balanced Multimodal Learning. neural information processing systems.DOI
  62. Da Wang, Yi Ma, Ting Guo, Hongyao Tang, Wei Wei, Jiye Liang (2025). FANS: A Flatness-Aware Network Structure for Generalization in Offline Reinforcement Learning. neural information processing systems.DOI
  63. Kaixuan Yao, Zhuo Li, Jianqing Liang, Jiye Liang, Ming Li, Feilong Cao (2025). HyperMixup: Hypergraph-Augmented with Higher-order Information Mixup. neural information processing systems.DOI
  64. Fuyuan Cao, Shichang Qiao, Kui Yu, Jiye Liang (2025). Automatic Visual Instrumental Variable Learning for Confounding-Resistant Domain Generalization. neural information processing systems.DOI
  65. Jing Liu, Fuyuan Cao, Xuechun Jing, Jiye Liang (2024). Deep multi-view graph clustering network with weighting mechanism and collaborative training. Expert Systems With Applications, Vol. 236.DOI
  66. 郭宇星，姚凯旋，王智强，温亮亮，梁吉业（2024）. 基于特征拓扑融合的黑盒图对抗攻击. 《计算机科学》.
  67. 王慧敏，王智强，郭婷，梁吉业（2024）. 一种基于主动学习的开放集图像识别方法. 《小型微型计算机系统》.
  68. 梁吉业，石川，徐童（2024）. 前言. 《计算机研究与发展》.
  69. 张凯涵，冯晨娇，姚凯旋，宋鹏，梁吉业（2024）. 基于对比学习和语义增强的多模态推荐算法. 《模式识别与人工智能》.
  70. 王婕婷，李飞江，李珏，钱宇华，梁吉业（2024）. 缓解随机一致性的基尼指数与决策树方法. 《中国科学:信息科学》.
  71. 赵兴旺，侯哲栋，姚凯旋，梁吉业（2024）. 基于注意力机制的两阶段融合多视图图聚类. 《清华大学学报(自然科学版)》.
  72. 王亚萍，王智强，王元龙，梁吉业（2024）. 基于协同训练的半监督图文关系抽取方法. 《南京理工大学学报》.
  73. 赵兴旺，张超，梁吉业（2024）. 融入模体信息的多层网络社区发现算法. 《南京大学学报(自然科学)》.
  74. 张鸽，闫京，魏巍，梁吉业（2024）. 基于样本旋转的生成困难样本的深度度量学习方法. 《山西大学学报(自然科学版)》.
  75. Zhihao Guo, Peng Song, Chenjiao Feng, Kaixuan Yao, Chuangyin Dang, Jiye Liang (2024). Causal intervention for knowledge graph denoising in recommender systems. International Journal of Machine Learning and Cybernetics.DOI
  76. Yue Bo Fan, Zhang Hu, Ru Li, Y X Wang, Guangjun Zhang, Hongye Tan, Jiye Liang (2024). Weakly-supervised explainable question answering via question aware contrastive learning and adaptive gate mechanism. Information Sciences.DOI
  77. Fuyuan Cao, Xuechun Jing, Kui Yu, Jiye Liang (2024). FWCEC: An Enhanced Feature Weighting Method via Causal Effect for Clustering. IEEE Transactions on Knowledge and Data Engineering.DOI
  78. Hangyuan Du, Wenjian Wang, Liang Bai, Lu Bai, Jiye Liang (2024). A motif based hypergraph multi-level semantic encoding framework for social recommender systems. Signal Processing.DOI
  79. Xianjie Guo, Kui Yu, Lin Liu, Jiuyong Li, Jiye Liang, Fuyuan Cao, Xindong Wu (2024). Progressive Skeleton Learning for Effective Local-to-Global Causal Structure Learning. IEEE Transactions on Knowledge and Data Engineering.DOI
  80. Zhuomin Liang, Liang Bai, Jinyu Fan, Xian Feng Yang, Jiye Liang (2024). Contrastive Learning With Enhancing Detailed Information for Pre-Training Vision Transformer. IEEE Transactions on Circuits and Systems for Video Technology.DOI
  81. Fuyuan Cao, Yunxia Wang, Kui Yu, Jiye Liang (2024). Causal Discovery From Unknown Interventional Datasets Over Overlapping Variable Sets. IEEE Transactions on Knowledge and Data Engineering.DOI
  82. Xingwang Zhao, Shujun Wang, Xiaolin Liu, Jiye Liang (2024). Multi-view clustering via dynamic unified bipartite graph learning. Pattern Recognition.DOI
  83. Yujia Zhang, Lin Li, Wei Wei, Yunpeng Lv, Jiye Liang (2024). A unified framework to control estimation error in reinforcement learning. Neural Networks.DOI
  84. Zijin Du, Jianqing Liang, Jiye Liang, Kaixuan Yao, Feilong Cao (2024). Graph Regulation Network for Point Cloud Segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence.DOI
  85. Yujia Zhang, Lin Li, Wei Wei, Xiu You, Jiye Liang (2024). Controlling estimation error in reinforcement learning via Reinforced Operation. Information Sciences.DOI
  86. Kaixuan Yao, Zijin Du, Ming Li, Feilong Cao, Jiye Liang (2024). Robust graph neural networks with Dirichlet regularization and residual connection. International Journal of Machine Learning and Cybernetics.DOI
  87. Liangliang Wen, Jiye Liang, Kaixuan Yao, Zhiqiang Wang (2024). Black-Box Adversarial Attack on Graph Neural Networks With Node Voting Mechanism. IEEE Transactions on Knowledge and Data Engineering.DOI
  88. Wei Wei, Da Wang, Lin Li, Jiye Liang (2024). Re-attentive experience replay in off-policy reinforcement learning. Machine Learning.DOI
  89. Yujie Wang, Kui Yu, Goh Yu Xiang, Fuyuan Cao, Jiye Liang (2024). Discovering causally invariant features for out-of-distribution generalization. Pattern Recognition.DOI
  90. Yujie Wang, Zhang Hu, Jiye Liang, Ru Li (2024). Heterogeneous-Graph Reasoning With Context Paraphrase for Commonsense Question Answering. IEEE/ACM Transactions on Audio Speech and Language Processing.DOI
  91. Yue Bo Fan, Hu Zhang, Ru Li, Yujie Wang, Tan Hongye, Jiye Liang (2024). FRVA: Fact-Retrieval and Verification Augmented Entailment Tree Generation for Explainable Question Answering.DOI
  92. 王元龙，雷鸣，王智强，张虎，李茹，梁吉业（2023）. 基于标签层次结构的视觉关系检测模型. 《电子学报》.
  93. 赵兴旺，张珧溥，梁吉业（2023）. 基于2阶段集成的多层网络社区发现算法. 《计算机研究与发展》.
  94. 王聪，王杰，刘全明，梁吉业（2023）. 生成样本对抗训练的图半监督学习. 《计算机科学与探索》.
  95. 李雅琪，王杰，王锋，梁吉业（2023）. 基于层次对比学习的半监督节点分类算法. 《模式识别与人工智能》.
  96. 闫涛，钱宇华，李飞江，闫泓任，王婕婷，梁吉业，郑珂银，吴鹏，陈路，胡治国，乔志伟，张江峰，翟小鹏（2023）. 三维时频变换视角的智能微观三维形貌重建方法. 《中国科学:信息科学》.
  97. Shujing Yang, Fuyuan Cao, Kui Yu, Jiye Liang (2023). Learning Causal Chain Graph Structure via Alternate Learning and Double Pruning. IEEE Transactions on Big Data.DOI
  98. Zhangjian Ji, Kai Feng, Yuhua Qian, Jiye Liang (2023). Sparse regularized correlation filter for UAV object tracking with adaptive contextual learning and keyfilter selection. Information Sciences.DOI
  99. Zhiqiang Li, Jie Wang, Jiye Liang (2023). Debiased graph contrastive learning based on positive and unlabeled learning. International Journal of Machine Learning and Cybernetics.DOI
  100. Feng Wang, Xinhao Wang, Wei Wei, Jiye Liang (2023). An incremental feature selection approach for dynamic feature variation. Neurocomputing.DOI
  101. Yecheng Guo, Liang Bai, Xian Feng Yang, Jiye Liang (2023). Improving Image Contrastive Clustering Through Self-Learning Pairwise Constraints. IEEE Transactions on Neural Networks and Learning Systems.DOI
  102. Haijun Zhang, Xian Feng Yang, Liang Bai, Jiye Liang (2023). Enhancing Drug Recommendations Via Heterogeneous Graph Representation Learning in EHR Networks. IEEE Transactions on Knowledge and Data Engineering.DOI
  103. Liancheng He, Liang Bai, Xian Feng Yang, Zhuomin Liang, Jiye Liang (2023). Exploring the role of edge distribution in graph convolutional networks. Neural Networks.DOI
  104. Liang Bai, Jiye Liang (2023). K-Relations-Based Consensus Clustering With Entropy-Norm Regularizers. IEEE Transactions on Neural Networks and Learning Systems.DOI
  105. Qin Yue, Junbiao Cui, Liang Bai, Jianqing Liang, Jiye Liang (2023). A zero-shot learning boosting framework via concept-constrained clustering. Pattern Recognition.DOI
  106. Lin Li, Yuze Li, Wei Wei, Yujia Zhang, Jiye Liang (2023). Multi-actor mechanism for actor-critic reinforcement learning. Information Sciences.DOI
  107. Fuyuan Cao, Qingqiang Chen, Ying Xing, Jiye Liang (2023). Efficient Classification by Removing Bayesian Confusing Samples. IEEE Transactions on Knowledge and Data Engineering.DOI
  108. Jiye Liang, Zijin Du, Jianqing Liang, Kaixuan Yao, Feilong Cao (2023). Long and Short-Range Dependency Graph Structure Learning Framework on Point Cloud. IEEE Transactions on Pattern Analysis and Machine Intelligence.DOI
  109. Ting Guo, Jiye Liang, Guo-Sen Xie (2023). Swap-Reconstruction Autoencoder for Compositional Zero-Shot Learning. IEEE International Conference on Multimedia and Expo (ICME).DOI
  110. Yuling Li, Kui Yu, Yuhong Zhang, Jiye Liang, Xindong Wu (2023). Adaptive Prototype Interaction Network for Few-Shot Knowledge Graph Completion. IEEE Transactions on Neural Networks and Learning Systems.DOI
  111. Jianli Huang, Xianjie Guo, Kui Yu, Fuyuan Cao, Jiye Liang (2023). Towards Privacy-Aware Causal Structure Learning in Federated Setting. IEEE Transactions on Big Data.DOI
  112. Jieting Wang, Feijiang Li, Jue Li, Chenping Hou, Yuhua Qian, Jiye Liang (2023). RSS-Bagging: Improving Generalization Through the Fisher Information of Training Data. IEEE Transactions on Neural Networks and Learning Systems.DOI
  113. Ting Guo, Jiye Liang, Guo-Sen Xie (2023). Group-wise interactive region learning for zero-shot recognition. Information Sciences.DOI
  114. Liang Bai, Minxue Qi, Jiye Liang (2023). Spectral clustering with robust self-learning constraints. Artificial Intelligence.DOI
  115. Jing Yan, Wei Wei, Xinyao Guo, Chuangyin Dang, Jiye Liang (2023). A bi-level metric learning framework via self-paced learning weighting. Pattern Recognition.DOI
  116. Shenggui Tang, Kaixuan Yao, Jianqing Liang, Zhiqiang Wang, Jiye Liang (2023). Graph Neural Networks with Interlayer Feature Representation for Image Super-Resolution.DOI
  117. Liancheng He, Liang Bai, Xian Feng Yang, Hangyuan Du, Jiye Liang (2023). High-order graph attention network. Information Sciences.DOI
  118. Feng Wang, Jiye Liang, Peng Song (2023). Coupling learning for feature selection in categorical data. International Journal of Machine Learning and Cybernetics.DOI
  119. Qingqiang Chen, Fuyuan Cao, Ying Xing, Jiye Liang (2023). Evaluating Classification Model Against Bayes Error Rate. IEEE Transactions on Pattern Analysis and Machine Intelligence.DOI
  120. Yujie Wang, Zhang Hu, Jiye Liang, Ru Li (2023). Dynamic Heterogeneous-Graph Reasoning with Language Models and Knowledge Representation Learning for Commonsense Question Answering. Annual Meeting of the Association for Computational Linguistics (ACL).DOI
  121. 冯晨娇，宋鹏，张凯涵，梁吉业（2022）. 融合社交网络信息的长尾推荐方法. 《模式识别与人工智能》.
  122. 王杰，张松岩，梁吉业（2022）. 融合一致性正则与流形正则的半监督深度学习算法. 《大数据》.
  123. 崔彩霞，王杰，庞天杰，梁吉业（2022）. 基于自监督学习的不平衡节点分类算法. 《模式识别与人工智能》.
  124. 韩露，郭鑫垚，魏巍，梁吉业（2022）. 基于约束分层加权的多度量学习算法. 《山东大学学报(理学版)》.
  125. 梁吉业，刘晓琳（2022）. 多视图聚类研究进展与展望. 《山西大学学报(自然科学版)》.
  126. 王克琪，钱宇华，梁吉业，刘畅，黄琴，陈路，贾洁茹（2022）. 局部–全局关系耦合的低照度图像增强. 《中国科学:信息科学》.
  127. Xinyao Guo, Lin Ji Li, Chuangyin Dang, Jiye Liang, Wei Wei (2022). Multiple metric learning via local metric fusion. Information Sciences.DOI
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  264. 史倩玉，梁吉业，赵兴旺（2016）. 一种不完备混合数据集成聚类算法. 《计算机研究与发展》.
  265. 赵兴旺，梁吉业（2016）. 一种基于信息熵的混合数据属性加权聚类算法. 《计算机研究与发展》.
  266. 郭兰杰，梁吉业，赵兴旺（2016）. 融合社交网络信息的协同过滤推荐算法. 《模式识别与人工智能》.
  267. 梁晋，梁吉业，赵兴旺（2016）. 一种面向大规模社会网络的社区发现算法. 《南京大学学报(自然科学)》.
  268. 李佳，梁吉业，庞天杰（2016）. 一种基于优势粗糙集的多属性决策排序方法. 《南京大学学报(自然科学)》.
  269. 孟娜，梁吉业，庞天杰（2016）. 一种基于抽样的谱聚类集成算法. 《南京大学学报(自然科学)》.
  270. 宋鹏，梁吉业，李常洪（2016）. 基于序化机理的稳健型股票价值投资决策——一个研究框架. 《北京理工大学学报：社会科学版》, No. 3.下载原文
  271. 梁吉业，钱宇华，李德玉，胡清华（2016）. 面向大数据的粒计算理论与方法研究进展. 《大数据》.
  272. 苗夺谦，张清华，钱宇华，梁吉业，王国胤，吴伟志，高阳，商琳，顾沈明，张红云（2016）. 从人类智能到机器实现模型——粒计算理论与方法. 《智能系统学报》.
  273. Yuhua Qian, Xinyan Liang, Guoping Lin, Qian Jian Guo, Jiye Liang (2016). Local multigranulation decision-theoretic rough sets. International Journal of Approximate Reasoning.DOI
  274. Yuhua Qian, Honghong Cheng, Jieting Wang, Jiye Liang, Witold Pedrycz, Chuangyin Dang (2016). Grouping granular structures in human granulation intelligence. Information Sciences.DOI
  275. Fuyuan Cao, Joshua Zhexue Huang, Jiye Liang (2016). A fuzzy SV- k -modes algorithm for clustering categorical data with set-valued attributes. Applied Mathematics and Computation.DOI
  276. Zhiqiang Wang, Jiye Liang, Ru Li, Yuhua Qian (2016). An Approach to Cold-Start Link Prediction: Establishing Connections between Non-Topological and Topological Information. IEEE Transactions on Knowledge and Data Engineering.DOI
  277. Liang Bai, Xueqi Cheng, Jiye Liang, Huawei Shen (2016). An Optimization Model for Clustering Categorical Data Streams with Drifting Concepts. IEEE Transactions on Knowledge and Data Engineering.DOI
  278. Wei Wei, Junbiao Cui, Jiye Liang, Wang Junhong (2016). Fuzzy rough approximations for set-valued data. Information Sciences.DOI
  279. Feng Wang, Jiye Liang (2016). An efficient feature selection algorithm for hybrid data. Neurocomputing.DOI
  280. Yinfeng Meng, Jiye Liang, Yuhua Qian (2016). Comparison study of orthonormal representations of functional data in classification. Knowledge-Based Systems.DOI
  281. Jun-Hong Wang, Yun-Qian Miao, Alaa M. Khamis, Fakhri Karray, Jiye Liang (2016). Adaptation Approaches in Unsupervised Learning: A Survey of the State-of-the-Art and Future Directions. Lecture notes in computer science.DOI
  282. 燕蜻，梁吉业，宋鹏（2015）. 一种基于相容关系的群体共识达成方法. 《控制与决策》.DOI
  283. 林国平，梁吉业，李进金（2015）. 多源决策信息系统的决策规则性能评价. 《模式识别与人工智能》.
  284. 王杰，梁吉业，郑文萍（2015）. 一种面向蛋白质复合体检测的图聚类方法. 《计算机研究与发展》.
  285. 梁吉业，钱宇华，李德玉，胡清华（2015）. 大数据挖掘的粒计算理论与方法. 《中国科学:信息科学》.
  286. 高嘉伟，梁吉业，刘杨磊，李茹（2015）. 一种基于Tri-training的半监督多标记学习文档分类算法. 《中文信息学报》.
  287. Guoping Lin, Jiye Liang, Yuhua Qian, Jinjin Li (2015). A fuzzy multigranulation decision-theoretic approach to multi-source fuzzy information systems. Knowledge-Based Systems.DOI
  288. Yuhua Qian, Feijiang Li, Jiye Liang, Bing Liu, Chuangyin Dang (2015). Space Structure and Clustering of Categorical Data. IEEE Transactions on Neural Networks and Learning Systems.DOI
  289. Yanli Sang, Jiye Liang, Yuhua Qian (2015). Decision-theoretic rough sets under dynamic granulation. Knowledge-Based Systems.DOI
  290. Wei Wei, Junhong Wang, Jiye Liang, Xin Mi, Chuangyin Dang (2015). Compacted decision tables based attribute reduction. Knowledge-Based Systems.DOI
  291. Guoping Lin, Jiye Liang, Yuhua Qian (2015). Uncertainty Measures for Multigranulation Approximation Space. International Journal of Uncertainty Fuzziness and Knowledge-Based Systems.DOI
  292. Yuhua Qian, Hang Li Xu, Jiye Liang, Bing Liu, Jieting Wang (2015). Fusing Monotonic Decision Trees. IEEE Transactions on Knowledge and Data Engineering.DOI
  293. Guoping Lin, Jiye Liang, Yuhua Qian (2015). An information fusion approach by combining multigranulation rough sets and evidence theory. Information Sciences.DOI
  294. Yuhua Qian, Yebin Li, Jiye Liang, Guoping Lin, Chuangyin Dang (2015). Fuzzy Granular Structure Distance. IEEE Transactions on Fuzzy Systems.DOI
  295. Baoli Wang, Jiye Liang, Yuhua Qian, Chuangyin Dang (2015). A Normalized Numerical Scaling Method for the Unbalanced Multi-Granular Linguistic Sets. International Journal of Uncertainty Fuzziness and Knowledge-Based Systems.DOI
  296. Jiye Liang (2015). Decision-Oriented Rough Set Methods. Lecture notes in computer science.DOI
  297. 张佳乐，梁吉业，庞继芳，王宝丽（2014）. 基于行为和评分相似性的关联规则群推荐算法. 《计算机科学》.
  298. 林国平，梁吉业，钱宇华（2014）. 基于多粒度视角下的D-S证据理论融合策略. 《计算机科学》.
  299. 郭一鹏，梁吉业，赵兴旺（2014）. 基于MapReduce的混合数据孤立点检测算法. 《小型微型计算机系统》.
  300. 孟银凤，梁吉业（2014）. 基于最小二乘支持向量机的函数型数据回归分析. 《模式识别与人工智能》.
  301. 孟银凤，梁吉业（2014）. 对中国各行业年平均工资的函数性数据分析. 《山西大学学报(自然科学版)》.
  302. Xiaofang Gao, Jiye Liang (2014). An improved incremental nonlinear dimensionality reduction for isometric data embedding. Information Processing Letters.DOI
  303. Liang Bai, Jiye Liang (2014). Cluster validity functions for categorical data: a solution-space perspective. Data Mining and Knowledge Discovery.DOI
  304. Baoli Wang, Jiye Liang, Yuhua Qian (2014). Determining decision makers’ weights in group ranking: a granular computing method. International Journal of Machine Learning and Cybernetics.DOI
  305. Yuhua Qian, Qi Wang, Honghong Cheng, Jiye Liang, Chuangyin Dang (2014). Fuzzy-rough feature selection accelerator. Fuzzy Sets and Systems.DOI
  306. Fuyuan Cao, Joshua Zhexue Huang, Jiye Liang (2014). Trend analysis of categorical data streams with a concept change method. Information Sciences.DOI
  307. Liang Bai, Jiye Liang (2014). The k-modes type clustering plus between-cluster information for categorical data. Neurocomputing.DOI
  308. Yuhua Qian, Shunyong Li, Jiye Liang, Zhongzhi Shi, Feng Wang (2014). Pessimistic rough set based decisions: A multigranulation fusion strategy. Information Sciences.DOI
  309. Baoli Wang, Jiye Liang (2014). A Novel Intelligent Multi-attribute Three-Way Group Sorting Method Based on Dempster-Shafer Theory. Lecture notes in computer science.DOI
  310. Baoli Wang, Jiye Liang, Yuhua Qian (2014). Preorder Information Based Attributes' Weights Learning in Multi-attribute Decision Making. Fundamenta Informaticae.DOI
  311. 李茹，王智强，李双红，梁吉业，Collin Baker（2013）. 基于框架语义分析的汉语句子相似度计算. 《计算机研究与发展》.
  312. 钱宇华，成红红，张晓琴，梁吉业（2013）. 数据簸箕. 《计算机科学与探索》.
  313. 刘杨磊，梁吉业，高嘉伟，杨静（2013）. 基于Tri-training的半监督多标记学习算法. 《智能系统学报》.
  314. 高小方，梁吉业（2013）. 基于等维度独立多流形的DC-ISOMAP算法. 《新型工业化》.
  315. 许行，梁吉业，王宝丽（2013）. 基于双向有序互信息的单调分类决策树算法. 《南京大学学报(自然科学)》.
  316. Yuhua Qian, Zhang Hu, Feijiang Li, Qinghua Hu, Jiye Liang (2013). Set-based granular computing: A lattice model. International Journal of Approximate Reasoning.DOI
  317. Xingwang Zhao, Jiye Liang, Fuyuan Cao (2013). A simple and effective outlier detection algorithm for categorical data. International Journal of Machine Learning and Cybernetics.DOI
  318. Xin Liu, Yuhua Qian, Jiye Liang (2013). A rule-extraction framework under multigranulation rough sets. International Journal of Machine Learning and Cybernetics.DOI
  319. Liang Bai, Jiye Liang, Chao Sui, Chuangyin Dang (2013). Fast global k-means clustering based on local geometrical information. Information Sciences.DOI
  320. Wei Wei, Jiye Liang, Junhong Wang, Yuhua Qian (2013). Decision-relative discernibility matrices in the sense of entropies. International Journal of General Systems.DOI
  321. Guoping Lin, Jiye Liang, Yuhua Qian (2013). Multigranulation rough sets: From partition to covering. Information Sciences.DOI
  322. Guoping Lin, Jiye Liang, Yuhua Qian (2013). Topological approach to multigranulation rough sets. International Journal of Machine Learning and Cybernetics.DOI
  323. Yuhua Qian, Zhang Hu, Yanli Sang, Jiye Liang (2013). Multigranulation decision-theoretic rough sets. International Journal of Approximate Reasoning.DOI
  324. Jiye Liang, Junrong Mi, Wei Wei, Feng Wang (2013). An accelerator for attribute reduction based on perspective of objects and attributes. Knowledge-Based Systems.DOI
  325. Wei Wei, Jiye Liang, Yuhua Qian, Chuangyin Dang (2013). Can fuzzy entropies be effective measures for evaluating the roughness of a rough set? Information Sciences.DOI
  326. Wei Wei, Jiye Liang, Yuhua Qian, Junhong Wang (2013). Fuzziness-Preserving Attribute Reduction from Hybrid Data. Lecture notes in computer science.DOI
  327. Liang Bai, Jiye Liang, Chuangyin Dang, Fuyuan Cao (2012). A cluster centers initialization method for clustering categorical data. Expert Systems With Applications, Vol. 39, No. 9.DOI
  328. Jifang Pang, Jiye Liang (2012). Evaluation of the results of multi-attribute group decision-making with linguistic information. Omega-International Journal Of Management Science, Vol. 40, No. 3.DOI
  329. 秦奇伟，梁吉业，钱宇华（2012）. 一种基于邻域距离的聚类特征选择方法. 《计算机科学》.
  330. 白雪飞，王文剑，梁吉业（2012）. 基于区域显著性的活动轮廓分割模型. 《计算机研究与发展》.
  331. 杨静，高嘉伟，梁吉业，刘杨磊（2012）. 基于数据场的改进DBSCAN聚类算法. 《计算机科学与探索》.
  332. 梁吉业，李超伟，魏巍（2012）. 基于Rough Sets的特征选择研究进展. 《山西大学学报(自然科学版)》.
  333. 常瑜，梁吉业，高嘉伟，杨静（2012）. 一种基于Seeds集和成对约束的半监督聚类算法. 《南京大学学报(自然科学)》.
  334. Fuyuan Cao, Jiye Liang, Deyu Li, Xingwang Zhao (2012). A weighting k-modes algorithm for subspace clustering of categorical data. Neurocomputing.DOI
  335. Feng Wang, Jiye Liang, Yuhua Qian (2012). Attribute reduction: A dimension incremental strategy. Knowledge-Based Systems.DOI
  336. Liang Bai, Jiye Liang, Chuangyin Dang, Fuyuan Cao (2012). The impact of cluster representatives on the convergence of the K-modes type clustering. IEEE Transactions on Pattern Analysis and Machine Intelligence.DOI
  337. Jiye Liang, Feng Wang, Chuangyin Dang, Yuhua Qian (2012). A Group Incremental Approach to Feature Selection Applying Rough Set Technique. IEEE Transactions on Knowledge and Data Engineering.DOI
  338. Feng Wang, Jiye Liang, Chuangyin Dang (2012). Attribute reduction for dynamic data sets. Applied Soft Computing.DOI
  339. Wei Wei, Jiye Liang, Yuhua Qian, Feng Wang (2012). Variable precision multi-granulation rough set. IEEE International Conference on Granular Computing (GrC).DOI
  340. Jiye Liang (2012). Feature selection for large-scale data sets in GrC. IEEE International Conference on Granular Computing (GrC).DOI
  341. Liang Bai, Jiye Liang, Chuangyin Dang, Fuyuan Cao (2012). A novel fuzzy clustering algorithm with between-cluster information for categorical data. Fuzzy Sets and Systems.DOI
  342. Yuhua Qian, Jiye Liang, Peng Song, Chuangyin Dang, Wei Wei (2012). Evaluation of the decision performance of the decision rule set from an ordered decision table. Knowledge-Based Systems.DOI
  343. Yuhua Qian, Jiye Liang, Wei Wei (2012). Consistency-preserving attribute reduction in fuzzy rough set framework. International Journal of Machine Learning and Cybernetics.DOI
  344. Jiye Liang, Feng Wang, Chuangyin Dang, Yuhua Qian (2012). An efficient rough feature selection algorithm with a multi-granulation view. International Journal of Approximate Reasoning.DOI
  345. Jiye Liang, Liang Bai, Chuangyin Dang, Fuyuan Cao (2012). The $K$-Means-Type Algorithms Versus Imbalanced Data Distributions. IEEE Transactions on Fuzzy Systems.DOI
  346. Junhong Wang, Jiye Liang, Yuhua Qian (2012). Closed-Label Concept Lattice Based Rule Extraction Approach. Lecture notes in computer science.DOI
  347. Fuyuan Cao, Jiye Liang (2011). A data labeling method for clustering categorical data. Expert Systems With Applications, Vol. 38, No. 3.DOI
  348. 刘薇，梁吉业，魏巍，钱宇华（2011）. 一种基于条件熵的增量式属性约简算法. 《计算机科学》.
  349. 钱宇华，梁吉业，王锋（2011）. 面向非完备决策表的正向近似特征选择加速算法. 《计算机学报》.
  350. 谭红叶，郑家恒，梁吉业（2011）. 时间关系识别研究进展. 《中文信息学报》.
  351. 燕蜻，梁吉业（2011）. 混合多属性群决策中的群体一致性分析方法. 《中国管理科学》, Vol. 19, No. 6.下载原文
  352. 闫麟，梁吉业，王俊红（2011）. 一种基于等价描述矩阵的规则提取方法. 《广西师范大学学报(自然科学版)》.
  353. 孟银凤，梁吉业，原曦曦（2011）. 函数性数据分析中的主成分分析. 《山西大学学报(自然科学版)》.
  354. Jiye Liang, Xingwang Zhao, Deyu Li, Fuyuan Cao, Chuangyin Dang (2011). Determining the number of clusters using information entropy for mixed data. Pattern Recognition.DOI
  355. Wei Wei, Jiye Liang, Yuhua Qian (2011). A comparative study of rough sets for hybrid data. Information Sciences.DOI
  356. Jiye Liang, Ru Li, Yuhua Qian (2011). Distance: A more comprehensible perspective for measures in rough set theory. Knowledge-Based Systems.DOI
  357. Peng Song, Jiye Liang, Yuhua Qian (2011). A two-grade approach to ranking interval data. Knowledge-Based Systems.DOI
  358. Yuhua Qian, Jiye Liang (2011). How to organize data with measurement errors? Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics.DOI
  359. Fuyuan Cao, Jiye Liang, Deyu Li, Liang Bai, Chuangyin Dang (2011). A dissimilarity measure for the k-Modes clustering algorithm. Knowledge-Based Systems.DOI
  360. Liang Bai, Jiye Liang, Chuangyin Dang, Fuyuan Cao (2011). A novel attribute weighting algorithm for clustering high-dimensional categorical data. Pattern Recognition.DOI
  361. Liang Bai, Jiye Liang, Chuangyin Dang (2011). An initialization method to simultaneously find initial cluster centers and the number of clusters for clustering categorical data. Knowledge-Based Systems.DOI
  362. Yuhua Qian, Jiye Liang, Witold Pedrycz, Chuangyin Dang (2011). An efficient accelerator for attribute reduction from incomplete data in rough set framework. Pattern Recognition.DOI
  363. Jiye Liang (2011). Uncertainty and Feature Selection in Rough Set Theory. Lecture notes in computer science.DOI
  364. Yuhua Qian, Chao Li, Jiye Liang (2011). An Efficient Fuzzy-Rough Attribute Reduction Approach. Lecture notes in computer science.DOI
  365. Jiye Liang (2011). A Method for Consensus Analysis in Hybrid Multiple Attribute Group Decision Making. Zhongguo guanli kexue.
  366. 张剑妹，陶世群，梁吉业，曹峰（2010）. XML的结构完整性约束推理. 《计算机学报》.
  367. 梁吉业，白亮，曹付元（2010）. 基于新的距离度量的K-Modes聚类算法. 《计算机研究与发展》.
  368. 王锋，钱宇华，梁吉业（2010）. 序信息系统的启发式属性约简算法. 《计算机科学》.
  369. 马楠楠，梁吉业，王锋，钱宇华（2010）. 一种序决策表的特征选择算法. 《广西师范大学学报(自然科学版)》.
  370. 王国胤，苗夺谦，吴伟志，梁吉业（2010）. 不确定信息的粗糙集表示和处理. 《重庆邮电大学学报(自然科学版)》.
  371. Yuhua Qian, Jiye Liang, Wei-Zhi Wu, Chuangyin Dang (2010). Information Granularity in Fuzzy Binary GrC Model. IEEE Transactions on Fuzzy Systems.DOI
  372. Yuhua Qian, Chuangyin Dang, Jiye Liang, Wei-Zhi Wu (2010). Partial ordering of information granulations: a further investigation. Expert Systems.DOI
  373. Xiaofang Gao, Jiye Liang (2010). The dynamical neighborhood selection based on the sampling density and manifold curvature for isometric data embedding. Pattern Recognition Letters.DOI
  374. Hongxing Chen, Yuhua Qian, Jiye Liang, Wei Wei (2010). On Partial Order Relations in Granular Computing. IEEE International Conference on Granular Computing (GrC).DOI
  375. Wei Wei, Jiye Liang, Yuhua Qian, Feng Wang, Chuangyin Dang (2010). Comparative study of decision performance of decision tables induced by attribute reductions. International Journal of General Systems.DOI
  376. Junhong Wang, Jiye Liang, Yuhua Qian (2010). A heuristic method to attribute reduction for concept lattice. International Conference on Machine Learning and Cybernetics.DOI
  377. Fuyuan Cao, Jiye Liang, Liang Bai, Xingwang Zhao, Chuangyin Dang (2010). A Framework for Clustering Categorical Time-Evolving Data. IEEE Transactions on Fuzzy Systems.DOI
  378. Yuhua Qian, Jiye Liang, Deyu Li, Feng Wang, Nannan Ma (2010). Approximation reduction in inconsistent incomplete decision tables. Knowledge-Based Systems.DOI
  379. Jiye Liang (2010). Dynamical Neighborhood Algorithm Based on Sampling Density and Manifold Curvature. Jisuanji gongcheng.
  380. Fuyuan Cao, Jiye Liang, Liang Bai (2009). A new initialization method for categorical data clustering. Expert Systems With Applications, Vol. 36, No. 7.DOI
  381. 曲开社，田永生，翟岩慧，梁吉业（2009）. 形式背景的BAM神经网络模型及模型上的概念生成. 《计算机科学》.
  382. 王俊红，梁吉业，曲开社（2009）. 基于优势关系的概念格. 《计算机科学》.
  383. 曲开社，梁亮，梁吉业，李德玉，陈红星（2009）. 形式概念分析的概念之间包含度理论. 《计算机科学》.
  384. 白亮，梁吉业，曹付元（2009）. 基于粗糙集的改进K-Modes聚类算法. 《计算机科学》.
  385. 桑妍丽，梁吉业（2009）. 基于粗糙信息向量的一种决策规则获取算法. 《计算机工程与应用》.
  386. 王俊红，梁吉业，曲开社（2009）. 基于优势关系的信息系统与形式概念分析. 《计算机应用》.
  387. 宋鹏，梁吉业，曹付元（2009）. 基于邻域粗糙集的企业财务危机预警指标选择. 《经济管理》, No. 8.下载原文
  388. 李茹，王文晶，梁吉业，宋小香，刘海静，由丽萍（2009）. 基于汉语框架网的旅游信息问答系统设计. 《中文信息学报》.
  389. Yuhua Qian, Jiye Liang, Chuangyin Dang (2009). Incomplete Multigranulation Rough Set. IEEE Transactions on Systems Man and Cybernetics - Part A Systems and Humans.DOI
  390. Yuhua Qian, Jiye Liang, Feng Wang (2009). A NEW METHOD FOR MEASURING THE UNCERTAINTY IN INCOMPLETE INFORMATION SYSTEMS. International Journal of Uncertainty Fuzziness and Knowledge-Based Systems.DOI
  391. Yuhua Qian, Jiye Liang, Wei Wei (2009). Accelerating incomplete feature selection. International Conference on Machine Learning and Cybernetics.DOI
  392. Fuyuan Cao, Jiye Liang, Guang Jiang (2009). An initialization method for the K -Means algorithm using neighborhood model. Computers & Mathematics with Applications.DOI
  393. Wei Wei, Jiye Liang, Yuhua Qian, Feng Wang (2009). An attribute reduction approach and its accelerated version for hybrid data. IEEE International Conference on Cognitive Informatics.DOI
  394. Yuhua Qian, Chuangyin Dang, Jiye Liang, Dawei Tang (2009). Set-valued ordered information systems. Information Sciences.DOI
  395. Jiye Liang (2009). Fuzzy K-Modes Clustering Algorithm Based on New Dissimilarity Measure. Jisuanji gongcheng.
  396. Jiye Liang (2009). BAM Models of Formal Contexts and Generating Concepts on the Models.
  397. 高嘉伟，梁吉业（2008）. 非平衡数据集分类问题研究进展. 《计算机科学》.
  398. 曹付元，梁吉业，姜广（2008）. 基于邻域模型的K-means初始聚类中心选择算法. 《计算机科学》.
  399. 梁吉业，魏巍，钱宇华（2008）. 一种基于条件熵的增量核求解方法. 《系统工程理论与实践》, Vol. 28, No. 4.下载原文
  400. Jiye Liang, Jun Wang, Yu Xia Qian (2008). A new measure of uncertainty based on knowledge granulation for rough sets. Information Sciences.DOI
  401. Chuangyin Dang, Wei Ma, Jiye Liang (2008). A deterministic annealing algorithm for approximating a solution of the min-bisection problem. Neural Networks.DOI
  402. Yuhua Qian, Jiye Liang, Chuangyin Dang (2008). Knowledge structure, knowledge granulation and knowledge distance in a knowledge base. International Journal of Approximate Reasoning.DOI
  403. Guoyin Wang, Qinghua Zhang, Houkuan Huang, Dongyi Ye, Qinghua Hu, Xuegang Hu, Zhongzhi Shi, Yongli Li, Lin Shang, Liping An, Ying Sai, Shanben Chen, Jiye Liang, Keyun Qin, Huanglin Zeng, Keming Xie, Duoqian Miao, Fan Min, Zhaocong Wu, Wei-Zhi Wu, Jianhua Dai (2008). Research on Rough Set Theory and Applications in China. Transactions on rough sets.DOI
  404. Wei Wei, Jiye Liang, Yuhua Qian (2008). Change mechanism of a decision table’s decision performance caused by attribute reductions. IEEE International Conference on Granular Computing (GrC).DOI
  405. Jiye Liang, Yuhua Qian (2008). Information granules and entropy theory in information systems. Science in China Series F Information Sciences.DOI
  406. Yuhua Qian, Jiye Liang, Chuangyin Dang (2008). Interval ordered information systems. Computers & Mathematics with Applications.DOI
  407. Yuhua Qian, Jiye Liang (2008). COMBINATION ENTROPY AND COMBINATION GRANULATION IN ROUGH SET THEORY. International Journal of Uncertainty Fuzziness and Knowledge-Based Systems.DOI
  408. Junhong Wang, Jiye Liang, Yuhua Qian, Chuangyin Dang (2008). UNCERTAINTY MEASURE OF ROUGH SETS BASED ON A KNOWLEDGE GRANULATION FOR INCOMPLETE INFORMATION SYSTEMS. International Journal of Uncertainty Fuzziness and Knowledge-Based Systems.DOI
  409. Yuhua Qian, Chuangyin Dang, Jiye Liang, Haiyun Zhang, Jian-Min Ma (2008). On the evaluation of the decision performance of an incomplete decision table. Data & Knowledge Engineering.DOI
  410. 王宝丽，梁吉业（2007）. 信息系统中的知识距离与知识粗糙熵. 《计算机科学》.
  411. 张海云，梁吉业，梁春华（2007）. 一种基于知识量的约简算法. 《小型微型计算机系统》.
  412. Yuhua Qian, Jiye Liang, Chuangyin Dang (2007). Consistency measure, inclusion degree and fuzzy measure in decision tables. Fuzzy Sets and Systems.DOI
  413. Yuhua Qian, Jiye Liang, Chuangyin Dang, Feng Wang, Wei Xu (2007). Knowledge distance in information systems. Journal of Systems Science and Systems Engineering.DOI
  414. Yuhua Qian, Jiye Liang, Xia Zhang, Chuangyin Dang (2007). Rough set approach under dynamic granulation in incomplete information systems.
  415. Yi Zhang, Jifang Pang, Jiahua Liang, Jiye Liang (2007). A method of knowledge acquisition based on the discernibility in imperfect information system. IEEE International Conference on Grey systems and Intelligent Services.DOI
  416. Yuhua Qian, Jiye Liang, Chuangyin Dang (2007). Converse approximation and rule extraction from decision tables in rough set theory. Computers & Mathematics with Applications.DOI
  417. Yuhua Qian, Jiye Liang, Deyu Li, Haiyun Zhang, Chuangyin Dang (2007). Measures for evaluating the decision performance of a decision table in rough set theory. Information Sciences.DOI
  418. Kwai‐Sang Chin, Jiye Liang, Chuangyin Dang (2007). Rough Set Data Analysis Algorithms for Incomplete Information Systems. Springer eBooks.DOI
  419. Yuhua Qian, Jiye Liang (2007). Evaluation Method for Decision Rule Sets. Lecture notes in computer science.DOI
  420. Jiye Liang (2007). Knowledge Inclusion Degree and Information Entropy of Rough Set Data Analysis. Journal of Shanxi University.
  421. Jiye Liang, Zhicai Shi, Deyu Li, Mark J. Wierman (2006). Information entropy, rough entropy and knowledge granulation in incomplete information systems. International Journal of General Systems.DOI
  422. Kaishe Qu, Yanhui Zhai, Jiye Liang, Min Chen (2006). Study of decision implications based on formal concept analysis. International Journal of General Systems.DOI
  423. Yuhua Qian, Jiye Liang (2006). Rough Set Method Based on Multi-Granulations. IEEE International Conference on Cognitive Informatics.DOI
  424. Yuhua Qian, Jiye Liang (2006). Combination Entropy and Combination Granulation in Incomplete Information System. Lecture notes in computer science.DOI
  425. Jiye Liang, Yuhua Qian (2006). Axiomatic Approach of Knowledge Granulation in Information System. Lecture notes in computer science.DOI
  426. Jiye Liang, Jifang Pang (2006). A Measure Method for Indiscernibility in Imperfect Information System. Advances in intelligent systems research/Advances in Intelligent Systems Research.DOI
  427. 曲开社，翟岩慧，李德玉，梁吉业（2005）. 信息系统同态的性质及上下近似的不变性. 《计算机科学》.
  428. 钱宇华，梁吉业，王江（2005）. 动态粒度下的粗糙集近似. 《计算机科学》.
  429. Jiye Liang, Yuhua Qian, Chengyuan Chu, Deyu Li, Junhong Wang (2005). Rough Set Approximation Based on Dynamic Granulation. Lecture notes in computer science.DOI
  430. 梁吉业，王俊红（2004）. 基于概念格的规则产生集挖掘算法. 《计算机研究与发展》.
  431. 李钝，亢临生，梁吉业（2004）. 使用粗糙集进行智能信息检索的方法. 《计算机工程》.
  432. 曹付元，梁吉业（2004）. 基于SQL语言的粗糙数据查询. 《计算机科学》.
  433. Jiye Liang, Zhongzhi Shi (2004). THE INFORMATION ENTROPY, ROUGH ENTROPY AND KNOWLEDGE GRANULATION IN ROUGH SET THEORY. International Journal of Uncertainty Fuzziness and Knowledge-Based Systems.DOI
  434. 曹飞龙，徐宗本，梁吉业（2003）. 多项式函数的神经网络逼近:网络的构造与逼近算法. 《计算机学报》.
  435. 张宏宇，梁吉业（2003）. 不完备信息系统下的变精度粗糙集模型及其知识约简算法. 《计算机科学》.
  436. Jiang Wang, Jiye Liang (2003). Rough set and rough classification based on imperfect information systems. World Congress on Intelligent Control and Automation.DOI
  437. Jiye Liang (2003). Concept Lattice and Rough Set. Journal of Shanxi University.
  438. Jiye Liang, Zongben Xu (2002). THE ALGORITHM ON KNOWLEDGE REDUCTION IN INCOMPLETE INFORMATION SYSTEMS. International Journal of Uncertainty Fuzziness and Knowledge-Based Systems.DOI
  439. Jiye Liang, Kwai‐Sang Chin, Chuangyin Dang, Richard C.M. Yam (2002). A new method for measuring uncertainty and fuzziness in rough set theory. International Journal of General Systems.DOI
  440. 梁吉业，徐宗本，李月香（2001）. 包含度与粗糙集数据分析中的度量. 《计算机学报》.
  441. 梁吉业，曲开社，徐宗本（2001）. 信息系统的属性约简. 《系统工程理论与实践》, Vol. 21, No. 12.下载原文
  442. 梁吉业（1996）. 求解线性与非线性方程组的单调异步迭代并行算法. 《计算机工程与设计》.

预印本

  1. Zihao Li, Xiaodong Yue, S. Y. Liu, Jiye Liang (2026). Three-Way Feature Encoding with Shadowed Prototypes. SSRN Electronic Journal.DOI
  2. Qin Yue, Junbiao Cui, Jianqing Liang, Liang Bai, Jiye Liang (2026). Zero-Shot Learning via Discriminative Semantic Assembly-Guided Sample Synthesis. SSRN Electronic Journal.DOI
  3. Jiao Zhao, Junbiao Cui, Bin Zheng, Jiye Liang (2025). Domain-Class Uncertainty-Aware Data Splitting for Domain Generalization. SSRN Electronic Journal.DOI

书籍章节

  1. Kaixuan Yao, Mingxu Zhang, Jiao Zhao, Junbiao Cui, Jiye Liang (2025). Cross-Channel Graph Attention Mechanism for Deep Convolutional Neural Networks. Frontiers in artificial intelligence and applications.DOI
  2. Jiye Liang, Yuhua Qian, Deyu Li (2010). Rule Extraction and Rule Evaluation Based on Granular Computing. IGI Global eBooks.DOI

研究方向

自动化技术计算机软件及计算机应用非线性科学与系统科学

此主页由公开资料整理，尚未经学者本人认领。