梁吉业 - 计算机与信息技术学院（大数据学院）

梁吉业，博士，教授，博士生导师，IEEE Fellow，中国计算机学会（CCF）会士，中国人工智能学会（CAAI）会士，山西大学学术委员会主任，山西大学计算智能与中文信息处理教育部重点实验室主任，曾任山西大学副校长（正校级）、太原师范学院院长。现任教育部科技委人工智能与区块链/科技伦理专门委员会委员，教育部高等学校计算机类专业教指委委员，中国计算机学会理事，中国人工智能学会常务理事，中国计算机学会人工智能与模式识别专委会主任，山西省计算机学会理事长，享受国务院政府特殊津贴专家。任国际学术期刊《Engineering Applications of Artificial Intelligence》，国内学术期刊《计算机研究与发展》、《模式识别与人工智能》与《智能系统学报》等期刊编委；是山西省高等学校优秀创新团队带头人、山西省首批科技创新重点团队带头人；入选山西省“三晋英才”支持计划高端领军人才、山西省高等学校中青年拔尖创新人才、山西省新世纪学术技术带头人333人才工程；获得山西省五一劳动奖章、山西省青年科学家奖、山西省模范教师、山西省优秀研究生导师等多项荣誉称号。

主要从事人工智能、机器学习、大数据分析挖掘等方面的教学科研工作。近年来先后主持科技部科技创新2030—“新一代人工智能”重大项目1项、国家自然科学基金/联合基金重点项目4项、国家863计划项目2项、国家自然科学基金面上项目6项等。先后在AI、JMLR、IEEE TPAMI、IEEE TKDE、ML、NeurIPS、ICML、CVPR、AAAI等国际国内重要学术期刊和会议发表论文400余篇，其中SCI收录300余篇。作为第一完成人获山西省自然科学一等奖3项、中国国际发明展览会金奖1项、山西省教学成果特等奖2项；作为第二完成人获山西省科技进步一等奖2项。2014—2023年连续入选爱思唯尔中国高被引学者榜单。指导的博士生获得全国百篇优秀博士学位论文提名奖、CCF优秀博士学位论文奖、中国人工智能学会优秀博士学位论文奖、中国中文信息学会优秀博士学位论文奖。

[1] Jianqing Liang, Min Chen, Jiye Liang*. Graph external attention enhanced transformer[C]. International Conference on Machine Learning, 2024

[2] Wei Wei, Da Wang, Lin Li, Jiye Liang*. Re-attentive experience replay in off-policy reinforcement learning[J]. Machine Learning, 113(5): 2327-2349 (2024)

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

[4] 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

[5] Liang Bai, Minxue Qi, Jiye Liang*. Spectral clustering with robust self-learning constraints[J]. Artificial Intelligence, 2023, 320: 103924

[6] 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

[7] Fuyuan Cao, Qingqiang Chen*, Ying Xing, Jiye Liang. Efficient classification by removing bayesian confusing samples[J]. IEEE Transactions on Knowledge and Data Engineering, 2023, DOI: 10.1109/TKDE.2023.3303425

[8] Haijun Zhang, Xian Yang, Liang Bai*, Jiye Liang. Enhancing drug recommendations via heterogeneous graph representation learning in EHR networks[J]. IEEE Transactions on Knowledge and Data Engineering, 2023, DOI: 10.1109/TKDE.2023.3329025

[9] Yu Xie, Zhiguo Qin, Maoguo Gong, Bin Yu, Jiye Liang*. Random deep graph matching[J]. IEEE Transactions on Knowledge and Data Engineering, 2023, 35(10): 10411-10422

[10] Junbiao Cui, Jianqing Liang, Qin Yue, Jiye Liang*. A general representation learning framework with generalization performance guarantees[C]. ICML2023

[11] Wei Wei, Lijun Zhang, Lin Li, Huizhong Song, Jiye Liang*. Set-membership belief state-based reinforcement learning for POMDPs[C]. ICML2023

[12] Ming Li*, Sho Sonoda*, Feilong Cao, Yu Guang Wang, Jiye Liang. How powerful are shallow neural networks with bandlimited random weights?[C]. ICML2023

[13] Yujie Wang, Hu Zhang*, Jiye Liang*, Ru Li. Dynamic heterogeneous-graph reasoning with language models and knowledge representation learning for commonsense question answering[C]. ACL2023

[14] 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

[15] Yuling Li, Kui Yu*, Yuhong Zhang, Jiye Liang, Xindong Wu. Adaptive prototype interaction network for few-shot knowledge graph completion[J]. IEEE Transactions on Neural Networks and Learning Systems, 2023, DOI: 10.1109/TNNLS.2023.3283545

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

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

[18] Jieting Wang, Feijiang Li, Jue Li, Chenping Hou, Yuhua Qian*, Jiye Liang. RSS-bagging: improving generalization through the fisher information of training data[J]. IEEE Transactions on Neural Networks and Learning Systems, 2023, DOI: 10.1109/TNNLS.2023.3270559

[19] 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

[20] 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, 2023, DOI: 10.1109/TBDATA.2023.3346712

[21] Xingwang Zhao, Shujun Wang, Xiaolin Liu, Jiye Liang*. Joint spectral embedding multi-view clustering algorithm based on bipartite graphs[J]. Journal of Software, 2023, DOI: 10.13328/j.cnki.jos.006995.(in Chinese)

[22] Xingwang Zhao, Yaopu Zhang, Jiye Liang*. Two-stage ensemble-based community discovery algorithm in multilayer networks[J]. Journal of Computer Research and Development, 2023, 60(12): 2832-2843. (in Chinese)

[23] Tao Yan, Yuhua Qian*, Feijiang Li, Hongren Yan, Jieting Wang, Jiye Liang, et al. Intelligent microscopic 3D shape reconstruction method based on 3D time-frequency transformation[J]. Scientia Sinica Informationis, 2023, 53: 282-308. (in Chinese)

[24] Jieting Wang, Feijiang Li, Jue Li, Yuhua Qian*, Jiye Liang. Gini index and decision tree method with mitigating random consistency[J]. Scientia Sinica Informationis, DOI: 10.1360/SSI-2022-0337.(in Chinese)

[25] Junbiao Cui, Jiye Liang*. Fuzzy learning machine[C]. NeurIPS2022

[26] Liang Bai, Jiye Liang*, Yunxiao Zhao. Self-constrained spectral clustering[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022, 45(4): 5126-5138

[27] Xinyan Liang, Yuhua Qian*, Qian Guo, Honghong Cheng, Jiye Liang, AF: An association-based fusion method for multi-modal classification[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022, 44(12): 9236-9254

[28] Jieting Wang, Yuhua Qian*, Feijiang Li, Jiye Liang, Qingfu Zhang. Generalization performance of pure accuracy and its application in selective ensemble learning[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022, 45(2): 1798-1816

[29] Kaixuan Yao, Jiye Liang*, Jianqing Liang, Ming Li, Feilong Cao. Multi-view graph convolutional networks with attention mechanism[J]. Artificial Intelligence, 2022, 307: 103708

[30] Wei Wei, Yujia Zhang, Jiye Liang*, Lin Li, Yuze Li. Controlling underestimation bias in reinforcement learning via quasi-median operation[C]. AAAI2022

[31] Yunxia Wang, Fuyuan Cao*, Kui Yu, Jiye Liang. Efficient causal structure learning from multiple interventional datasets with unknown targets[C]. AAAI2022

[32] Qingqiang Chen, Fuyuan Cao*, Ying Xing, Jiye Liang. Instance selection: A bayesian decision theory perspective[C]. AAAI2022

[33] Qin Yue, Jiye Liang*, Junbiao Cui, Liang Bai. Dual bidirectional graph convolutional networks for zero-shot node classification[C]. KDD2022

[34] Yu Xie, Shengze Lv, Yuhua Qian*, Chao Wen, Jiye Liang. Active and semi-supervised graph neural networks for graph classification[J]. IEEE Transactions on Big Data, 2022, 8: 920-932

[35] Jie Wang, Jianqing Liang*, Jiye Liang, Kaixuan Yao. GUIDE: Training deep graph neural networks via guided dropout over edges[J]. IEEE Transactions on Neural Networks and Learning Systems, 35(4): 4465-4477 (2024)

[36] Xiaolin Liu, Liang Bai, Xingwang Zhao, Jiye Liang*. Incomplete multi-view clustering algorithm based on multi-order neighborhood diffusion and fusion[J]. Journal of Software, 2022, 33(4): 1354−1372. (in Chinese)

[37] 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

[38] Keqi Wang, Yuhua Qian*, Jiye Liang, Chang Liu, Qin Huang, et al. Local-global coupling relationship based low-light image enhancement[J]. Scientia Sinica Informationis, 2022, 52(3): 443-460. (in Chinese)

[39] 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

[40] Gaoxia Jiang, Wenjian Wang*, Yuhua Qian, Jiye Liang. A unified sample selection framework for output noise filtering: An error-bound perspective[J]. Journal of Machine Learning Research, 2021, 22(18): 1−66

[41] 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

[42] Chenjiao Feng, Peng Song, Zhiqiang Wang, Jiye Liang*. A method on long tail recommendation based on three-factor probabilistic graphical model[J]. Journal of Computer Research and Development, 2021, 58(9): 1975-1986. (in Chinese)

[43] Liang Bai, Jiye Liang*. Sparse subspace clustering with entropy-norm[C]. ICML2020

[44] Liang Bai, Jiye Liang*. A three-level optimization model for nonlinearly separable clustering[C]. AAAI2020

[45] Jing Liu, Fuyuan Cao, Xiaozhi Gao, Liqin Yu, Jiye Liang*. A cluster-weighted kernel K-Means method for multi-view clustering[C]. AAAI2020

[46] Yinfeng Meng, Jiye Liang*. Linear regularized functional logistic model[J]. Journal of Computer Research and Development, 2020, 57(8): 1617-1626. (In Chinese)

[47] Jiye Liang*, Yunsheng Song, Deyu Li, Zhiqiang Wang, Chuangyin Dang. An accelerator for the logistic regression algorithm based on sampling on-demand[J]. SCIENCE CHINA Information Sciences, 2020, 63(6): 169102

[48] Honghong Cheng, Yuhua Qian*, Zhiguo Hu, Jiye Liang. Association mining method based on neighborhood[J]. Scientia Sinica Informationis, 2020, 50(6): 824-844. (In Chinese)

[49] Feijiang Li, Yuhua Qian*, Jieting Wang, Jiye Liang, Wenjian Wang. Clustering method based on sample's stability[J]. Scientia Sinica Informationis, 2020, 50(8): 1239-1254. (In Chinese)

[50] Liang Bai, Jiye Liang*, Hangyuan Du, Yike Guo. An information-theoretical framework for cluster ensemble[J]. IEEE Transactions on Knowledge and Data Engineering, 2019, 31(8): 1464-1477

[51] Anhui Tan*, Weizhi Wu, Yuhua Qian, Jiye Liang, Jinkun Chen, et al. Intuitionistic fuzzy rough set-based granular structures and attribute subset selection[J]. IEEE Transactions on Fuzzy Systems, 2019, 27(3): 527-539

[52] Zhiqiang Wang, Jiye Liang*, Ru Li. Probability matrix factorization for link prediction based on information fusion[J]. Journal of Computer Research and Development, 2019, 56(2): 306-318. (In Chinese)

[53] Liang Bai, Jiye Liang*, Yike Guo. An ensemble clusterer of multiple fuzzy k-means clusterings to recognize arbitrarily shaped clusters[J]. IEEE Transactions on Fuzzy Systems, 2018, 26(6): 3524-3533

[54] Fuyuan Cao, Joshua Zhexue Huang*, Jiye Liang, Xingwang Zhao, Yinfeng Meng. An Algorithm for Clustering Categorical Data with Set-valued Features[J]. IEEE Transactions on Neural Networks and Learning Systems, 2018, 29(10): 4593-4606

[55] Jiye Liang*, Jie Qiao, Fuyuan Cao, Xiaolin Liu. A distributed representation model for short text analysis[J]. Journal of Computer Research and Development, 2018, 55(8): 1631-1640. (in Chinese)

[56] Qinghua Hu*, Yu Wang, Yucan Zhou, Hong Zhao, Yuhua Qian, Jiye Liang. Review on hierarchical learning methods for large-scale classification task[J]. Scientia Sinica Informationis, 2018, 48(5): 487-500. (In Chinese)

[57] Kaihan Zhang, Jiye Liang*, Xingwang Zhao, Zhiqiang Wang. A collaborative filtering recommendation algorithm based on information of community experts[J]. Journal of Computer Research and Development, 2018, 55(5): 968-976. (In Chinese)

[58] Yali Lü, Jiajie Wu, Jiye Liang, Yuhua Qian. Random search learning algorithm of BN based on super-structure[J]. Journal of Computer Research and Development, 2017, 54(11): 2558-2566. (In Chinese)

[59] Zhiqiang Wang, Jiye Liang*, Ru Li, Yuhua Qian. An approach to cold-start link prediction: establishing connections between non-topological and topological information[J]. IEEE Transactions on Knowledge and Data Engineering, 2016, 28(11): 2857-2870

[60] Liang Bai, Xueqi Cheng, Jiye Liang*, Huawei Shen. An optimization model for clustering categorical data streams with drifting concepts[J]. IEEE Transactions on Knowledge and Data Engineering, 2016, 28(11): 2871-2883

[61] Yuhua Qian, Feijiang Li, Jiye Liang, Bing Liu, Chuangyin Dang. Space structure and clustering of categorical data[J]. IEEE Transactions on Neural Networks and Learning Systems, 2016, 27(10): 2047-2059

[62] Xingwang Zhao, Jiye Liang*. An attribute weighted clustering algorithm for mixed data based on information entropy[J]. Journal of Computer Research and Development, 2016, 53(5): 1018-1028. (in Chinese)

[63] Qianyu Shi, Jiye Liang, Xingwang Zhao*. A clustering ensemble algorithm for incomplete mixed data[J]. Journal of Computer Research and Development, 2016, 53(9): 1979-1989. (in Chinese)

[64] Jiye Liang*, Chenjiao Feng, Peng Song. A survey on correlation analysis of big data[J]. Chinese Journal of Computers, 2016, 39(1): 1-18. (in Chinese)

[65] Zhiqiang Wang, Ru Li*, Jiye Liang, Xuhua Zhang, Juan Wu, et al. Research on question answering for reading comprehension based on Chinese discourse frame semantic parsing[J]. Chinese Journal of Computers, 2016, 39(4): 795-807. (in Chinese)

[66] Yuhua Qian, Yebin Li, Jiye Liang, Guoping Lin, Chuangyin Dang. Fuzzy granular structure distance[J]. IEEE Transactions on Fuzzy Systems, 2015, 23(6): 2245-2259

[67] Yuhua Qian, Hang Xu, Jiye Liang, Bing Liu, Jieting Wang. Fusing monotonic decision trees[J]. IEEE Transactions on Knowledge and Data Engineering, 2015, 27(10): 2717-2728

[68] Jiye Liang*, Yuhua Qian, Deyu Li, Qinghua Hu. Theory and method of granular computing for big data mining[J]. Scientia sinica informationis, 2015, 45(11): 1355-1369. (in Chinese)

[69] Jie Wang, Jiye Liang, Wenping Zheng*. A graph clustering method for detecting protein complexes[J]. Journal of Computer Research and Development, 2015, 52(8): 1784-1793. (in Chinese)

[70] Jiye Liang*, Feng Wang, Chuangyin Dang, Yuhua Qian. A group incremental approach to feature selection applying rough set technique[J]. IEEE Transactions on Knowledge and Data Engineering, 2014, 26(2): 294-308

[71] 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

[72] Xiaofang Gao, Jiye Liang*. Manifold learning algorithm DC-ISOMAP of data lying on the well-separated multi-manifold with same intrinsic dimension[J]. Journal of Computer Research and Development, 2013, 50(8): 1690-1699. (in Chinese)

[73] Ru Li, Zhiqiang Wang, Shuanghong Li, Jiye Liang, Collin Baker. Chinese Sentence Similarity Computing Based on Frame Semantic Parsing[J]. Journal of Computer Research and Development, 2013, 50(8): 1728-1736. (in Chinese)

[74] 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

[75] Xuefei Bai, Wenjian Wang, Jiye Liang*. An active contour model based on region saliency for image segmentation[J]. Journal of Computer Research and Development, 2012, 49(12): 2686-2695. (in Chinese)

[76] Yuhua Qian, Jiye Liang*, Weizhi Wu, Chuangyin Dang. Information granularity in fuzzy binary GrC model[J]. IEEE Transactions on Fuzzy Systems, 2011, 19(2): 253-264

[77] Yuhua Qian, Jiye Liang*, Feng Wang. A positive approximation based accelerated algorithm to feature selection from incomplete decision tables[J]. Chinese Journal of Computers, 2011, 34(3): 435-442. (in Chinese)

[78] Yuhua Qian, Jiye Liang*, Witold Pedrycz, Chuangyin Dang. Positive approximation: an accelerator for attribute reduction in rough set theory[J]. Artificial Intelligence, 2010, 174: 597-618

[79] 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

[80] Yuhua Qian, Jiye Liang*, Chuangyin Dang. Incomplete multigranulation rough set[J]. IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans, 2010, 40(2): 420-431

[81] Jiye Liang*, Liang Bai, Fuyuan Cao. K-modes clustering algorithm based on a new distance measure[J]. Journal of Computer Research and Development, 2010, 47(10): 1749-1755. (in Chinese)

[82] Jianmei Zhang, Shiqun Tao, Jiye Liang, Feng Cao. Reasoning about Structural Integrity Constraints for XML[J]. Chinese Journal of Computers, 2010, 33(12): 2281-2290. (in Chinese)

[83] Kaishe Qu*, Yanhui Zhai, Jiye Liang, Deyu Li. Representation and extension of rough set theory Based on formal concept analysis[J]. Journal of Software, 2007, 18(9): 2174-2182. (in Chinese)

[84] Jiye Liang*, Junhong Wang. An algorithm for extracting rule-generating sets based on concept lattice[J]. Journal of Computer Research and Development, 2004, 41(8): 1339-1344. (in Chinese)

[85] Feilong Cao, Zongben Xu, Jiye Liang. Approximation of polynomial functions by neural network: construction of network and algorithm of approximation[J]. Chinese Journal of Computers, 2003, 26(8): 906-912. (in Chinese)

[86] Jiye Liang, Zongben Xu, Yuexiang Li. Inclusion degree and measures of rough set data analysis[J]. Chinese Journal of Computers, 2001, 24(5): 544-547. (in Chinese)

1. 国家自然科学基金委员会，联合基金重点项目，U21A20473，网络大数据分析挖掘的理论与方法，2022-01至2025-12，主持

2. 国家自然科学基金委员会，面上项目，62376141，知识引导的开放集学习方法研究，2024.01至2027.12，主持

3. 国家科技部，科技创新2030—“新一代人工智能”重大项目，2020AAA0106100，认知计算基础理论与方法研究，2020-11至2024-10，主持

4. 国家自然科学基金委员会，面上项目，61876103，基于多粒度的半监督学习方法，2019-01至2022-12，主持

5. 国家自然科学基金委员会，重点项目/总装联合基金项目，61432011/U1435212，面向大数据的粒计算理论与方法，2015-01至2019-12，主持

6. 国家自然科学基金委员会，重点项目，71031006，高维复杂数据分析理论及其在投资决策中的应用，2011-01至2014-12，主持

7. 国家科技部，973计划前期研究专项，2011CB11805，基于认知机理的高维复杂数据建模理论与方法，2011-01至2012-12，主持

8. 国家自然科学基金委员会，面上项目，70971080，面向复杂数据的粗糙集多属性/多准则决策分析研究，2010-01至2012-12，主持

9. 国家自然科学基金委员会，面上项目，60773133，复杂信息系统的粒度结构与知识获取研究，2008-01至2010-12，28万元，已结题，主持

10. 国家科技部，863计划项目，2007AA01Z165，面向高维复杂数据的粒度计算理论与算法研究，2007-10至2009-12，主持

11. 国家自然科学基金委员会，面上项目，70471003，基于软计算技术的不确定性决策方法研究，2005-01至2007-12，主持

12. 国家科技部，863计划项目，2004AA115460，专家系统及计算机软硬件系统评价技术研究，2004-10至2005-12，主持

13. 国家自然科学基金委员会，面上项目，60275019，粗糙集理论中的不确定性、模糊性与知识获取，2003-01至2005-12，主持