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李熙铭 ( 教授 ) 赞713 的个人主页 https://teachers.jlu.edu.cn/XimingLi/zh_CN/index.htm   教授 性别 : 男 学历 : 博士研究生毕业 学位 : 博士 在职信息 : 在职 所在单位 : 计算机科学与技术学院、网络安全学院 办公地点 : 吉林大学前卫南区 计算机楼 B527 个人简介 姓       名： 李熙铭职       称： 副教授院       系： 计算机科学与技术学院办公地点： 计算机楼B527联系方式： (+86)13944834897                  liximing86@gmail.com                  ximingli@jlu.edu.cn2015年博士毕业留校工作至今, 主要研究领域为人工智能、机器学习、自然语言处理。累计承担和参与国家和省部级科研项目10余项。累计发表学术论文50余篇，包括AAAI, ACL, WWW, IJCAI, CIKM, SDM, COLING, TNNLS, Machine Learning, KAIS等顶级会议和期刊。招收硕士研究生：欢迎有意报送和报考的硕士/博士研究生同学与我联系。具体要求如下：1.  对科研抱有热情。2.  有清晰的逻辑思维和健康的体魄。3.  有扎实的数学基础和熟练的英文读写能力。4.  乐观积极，坚忍不拔，有亲和力，表达能力强。5.  至少精通一门编程语言。2021/10/01 - One full paper has been accepted by WWW  Journal2021/08/26 - One full paper has been accepted by EMNLP2021/08/08 - Three full papers have been accepted by CIKM 2021/05/06 - One full paper has been accepted by ACL 2021/04/29 - One full paper has been accepted by IJCAI 2021/04/16 - One paper has been published by Machine Learning 代表性论文列表 (* 通讯作者)会议论文[1] Yiming Wang, Ximing Li*, Xiaotang Zhou and Jihong Ouyang. Extracting Topics with Simultaneous Word Co-occurrence and Semantic Correlation Graphs: Neural Topic Modeling for Short Texts. Conference on Empirical Methods in Natural Language Processing (EMNLP), 2021, in press. (Findings) CCF Rank B. [2] Changchun Li, Ximing Li*, Jihong Ouyang and Yiming Wang. Detecting the Fake Candidate Instances: Ambiguous Label Learning with Generative Adversarial Networks. ACM International Conference on Information and Knowledge Management (CIKM), 2021, in press. CCF Rank B.[3] Zhiqi Ge, Ximing Li*. To Be or not to Be, Tail Labels in Extreme Multi-label Learning. ACM International Conference on Information and Knowledge Management (CIKM), 2021, in press. CCF Rank B.[4] Renchu Guan, Yonghao Liu, Xiaoyue Feng* and Ximing Li*. VPALG: Paper-publication Prediction with Graph Neural Networks. ACM International Conference on Information and Knowledge Management (CIKM), 2021, in press. CCF Rank B.[5] Changchun Li, Ximing Li* and Jihong Ouyang. Semi-Supervised Text Classification with Balanced Deep Representation Distributions. The Joint Conference of the Association for Computational Linguistics (ACL), 2021, in press. CCF Rank A.[6] Yiming Wang, Ximing Li *, Jihong Ouyang. Layer-Assisted Neural Topic Modeling over Document Networks. International Joint Conference on Artificial Intelligence (IJCAI), 2021, in press. CCF Rank A.[7] Changchun Li, Ximing Li*, Jihong Ouyang and Yiming Wang. Semantics-assisted Wasserstein Learning for Topic and Word Embeddings. IEEE International Conference on Data Mining (ICDM), 2020, 292-301. CCF Rank B.[8] Changchun Li, Ximing Li* and Jihong Ouyang. Learning with Noisy Partial Labels by Simultaneously Leveraging Global and Local Consistencies. ACM International Conference on Information and Knowledge Management (CIKM), 2020, 725-734. CCF Rank B.[9] Ximing Li and Yang Wang. Recovering Accurate Labeling Information from Partially Valid Data for Effective Multi-Label Learning.  International Joint Conference on Artificial Intelligence (IJCAI), 2020, 1373-1380. CCF Rank A.[10] Yiyuan Wang, Shaowei Cai, Shiwei Pan, Ximing Li and Minghao Yin. Reduction and Local Search for Weighted Graph Coloring Problem. AAAI Conference on Artificial Intelligence (AAAI), 2020, 2433-2441. CCF Rank A.[11] Jianfeng Qu, Wen Hua, Dantong Ouyang, Xiaofang Zhou and Ximing Li. A Fine-grained and Noise-aware Method for Neural Relation Extraction. ACM International Conference on Information and Knowledge Management (CIKM), 2019, 659-668. CCF Rank B.[12] Jinjin Chi, Jihong Ouyang, Ximing Li*, Yang Wang and Meng Wang. Approximate Optimal Transport for Continuous Densities with Copulas. International Joint Conference on Artificial Intelligence (IJCAI), 2019, 2165-2171. CCF Rank A.[13] Changchun Li, Jihong Ouyang and Ximing Li*. Classifying Extremely Short Texts by Exploring Semantic Centroids in Word Mover’s Distance Space. The Web Conference (WWW), 2019, 939-949. CCF Rank A.[14] Ximing Li, Jiaojiao Zhang and Jihong Ouyang. Dirichlet Multinomial Mixture with Variational Manifold Regularization: Topic Modeling over Short Texts. AAAI Conference on Artificial Intelligence (AAAI), 2019, 7884-7891. CCF Rank A.[15] Ximing Li, Changchun Li, Jinjin Chi, Jihong Ouyang and Chenliang Li. Dataless Text Classification: A Topic Modeling Approach with Document Manifold. ACM International Conference on Information and Knowledge Management (CIKM), 2018, 973-982. CCF Rank B.[16] Ximing Li, Changchun Li, Jinjin Chi and Jihong Ouyang. Variance Reduction in Black-box Variational Inference by Adaptive Importance Sampling. International Joint Conference on Artificial Intelligence (IJCAI), 2018, 2404-2410. CCF Rank A.[17] Ximing Li and Bo Yang. A Pseudo Label based Dataless Naive Bayes Algorithm for Text Classification with Seed Words. International Conference on Computational Linguistics (COLING), 2018, 1908-1917. CCF Rank B.[18] Ximing Li, Changchun Li, Jinjin Chi, Jihong Ouyang and Wenting Wang. Black-box Expectation Propagation for Bayesian Models. SIAM International Conference on Data Mining (SDM), 2018, 603-611. CCF Rank B.[19] Ximing Li, Jinjin Chi, Changchun Li, Jihong Ouyang and Bo Fu. Integrating Topic Modeling with Word Embeddings by Mixtures of vMFs. International Conference on Computational Linguistics (COLING). 2016, 151-160. CCF Rank B.[20]  Ximing Li, Jihong Ouyang and Xiaotang Zhou. Sparse Hybrid Variational-Gibbs Algorithm for Latent Dirichlet Allocation. SIAM International Conference on Data Mining (SDM). 2016, 729-737. CCF Rank B.[21] Ximing Li, Jihong Ouyang and Xiaotang Zhou. Adaptive Centroid-based Algorithm for Document Clustering. International Symposium on Parallel Architectures, Algorithms and Programming. 2014, 63-68.[22]  Jihong Ouyang, You Lu and Ximing Li. Momentum Online LDA for Large-scale Datasets. European Conference on Artificial Intelligence (ECAI), 2014, 1075-1076. (short paper) CCF Rank B.期刊论文[1] Yiming Wang, Ximing Li*, Jihong Ouyang, Zeqi Guo, Yimeng Wang. Extracting Nonlinear Neural Topics with Neural Variational Bayes. World Wide Web Journal. 2021, in press. SCI, CCF Rank B.[2] Ximing Li, Yang Wang, Jihong Ouyang, Meng Wang. Topic Extraction from Extremely Short Texts with Variational Manifold Regularization. Machine Learning Journal. 2021, 110: 1029-1066. SCI, CCF Rank B[3] Chuangye Zhang, Yan Niu, Tie Ru and Ximing Li. Color Image Super-Resolution and Enhancement with Inter-Channel Details at Trivial Cost. Journal of Computer Science and Technology. 2020, 35, 889-899. SCI, CCF Rank B[4]  Ximing Li, Yang Wang, Zhao Zhang, Richang Hong and Meng Wang. RMoR-Aion: Robust Multi-output Regression by Simultaneously Alleviating Input and Output Noises. IEEE Transactions on Neural Networks and Learning Systems. 2021, 32(3): 1351-1364. SCI, CCF Rank B[5]  Zhijuan Xu, Xueyan Liu, Xianjuan Cui, Ximing Li and Bo Yang. Robust Stochastic Block Model. Neurocomputing. 2019, 379:398-412, SCI, CCF Rank C[6]  Jinjin Chi, Jihong Ouyang, Changchun Li, Xueyang Dong, Ximing Li* and Xinhua Wang. Topic Representation: Finding More Representative Words in Topic Models. Pattern Recognition Letters. 2019, 123:53-60, SCI, CCF Rank C [7]  Bo Fu, Xiaoyang Zhao, Chuanming Song, Ximing Li and Xiang-Hai Wang. A Salt and Pepper Noise Image Denoising Method based on the Generative Classification. Multimedia Tools and Applications. 2019, 78(9):12043-12053, SCI, CCF Rank C[8]  Ximing Li, Ang Zhang, Changchun Li, Lantian Guo, Wenting Wang and Jihong Ouyang. Relational Biterm Topic Model: Short Text Topic Modeling using Word Embeddings. The Computer Journal. 2019, 62(3):359-372, SCI, CCF Rank B[9]  Jinjin Chi, Jihong Ouyang, Ximing Li and Changchun Li. Empirical Study on Variational Inference Methods for Topic Models. Journal of Experimental Theoretical and Artificial. Intelligence. 2019, 30(1):129-142, SCI, CCF Rank C[10] Ximing Li, Ang Zhang, Changchun Li, Jihong Ouyang and Yi Cai. Exploring Coherent Topics by Topic Modeling with Term Weighting. Information Processing and Management. 2018, 54(6):1345-1358, SCI, CCF Rank B[11] Xiaotang Zhou, Jihong Ouyang and Ximing Li. Two Time-efficient Gibbs Sampling Inference Algorithms for Biterm Topic Model. Applied. Intelligence. 2018, 48(3):730-754, SCI, CCF Rank C[12] Xiaotang Zhou, Jihong Ouyang and Ximing Li. A More Time-efficient Gibbs Sampling Algorithm based on SparseLDA for Latent Dirichlet Allocation. Intelligent Data Analysis. 2018, 22(6):1227-1257, SCI, CCF Rank C[13] Ximing Li, Yue Wang, Ang Zhang, Changchun Li, Jinjin Chi and Jihong Ouyang. Filtering out the Noise in Short Text Topic Modeling. Information Sciences. 2018, 456:83-96, SCI, CCF Rank B[14] Ximing Li, Changchun Li, Jinjin Chi and Jihong Ouyang. Short text Topic Modeling by Exploring Original Documents. Knowledge and Information Systems. 2018, 56(2):443-462, SCI, CCF Rank B[15] Yue-peng Zou, Jihong Ouyang and Ximing Li*. Supervised Topic Models with Weighted Words: Multi-label Document Classification. Frontiers of Information Technology & Electronic Engineering. 2018, 19(4):513-523, SCI[16]  Jianfeng Qu, Dantong Ouyang, Wen Hua, Yuxin Ye and Ximing Li. Distant Supervision for Neural Relation Extraction Integrated with Word Attention and Property Features. Neural Networks. 2018, 100:59-69, SCI, CCF Rank B[17] Ximing Li and Jihong Ouyang. Tuning the Learning Rate for Stochastic Variational Inference. Journal of Computer Science and Technology. 2016, 31(2):428-436. SCI, CCF Rank B[18] Ximing Li, Jihong Ouyang and Xiaotang Zhou. A Kernel-based Centroid Classifier using Hypothesis Margin. Journal of Experimental & Theoretical Artificial Intelligence. 2016, 28(6):955-969. SCI, CCF Rank C[19] Jihong Ouyang, Ximing Li and Hongtu Li. Boosting scene understanding by hierarchical Pachinko allocation. Multimedia Tools and Applications. 2016, 75(20):12581-12595 SCI, CCF Rank C [20] Jihong Ouyang, Yanhui Liu, Ximing Li and Xiaotang Zhou. Multi-grain Sentiment/Topic Model based on LDA. Acta Electronica Sinica. 2015, 43(9):1875-1880.[21] Ximing Li, Jihong Ouyang and Xiaotang Zhou. Supervised Topic Models for Multi-label Classification. Neurocomputing, 2015, 149:811-819. SCI, CCF Rank C[22] Ximing Li, Jihong Ouyang, You Lu, Xiaotang Zhou and Tian Tian. Group Topic Model: Organizing Topics into Groups. Information Retrieval, 2015, 18(1):1-25. SCI, CCF Rank C[23] Ximing Li, Jihong Ouyang, Xiaotang Zhou, You Lu and Yanhui Liu. Supervised Labeled Latent Dirichlet Allocation for Document Categorization. Applied Intelligence, 2015, 42(3):581-593. SCI, CCF Rank C[24] Ximing Li, Jihong Ouyang and Xiaotang Zhou. Labelset Topic Model for Multi-label Document Classification. Journal of Intelligent Information Systems. 2016, 46(1):83-97. SCI, CCF Rank C[25] Ximing Li, Jihong Ouyang and Xiaotang Zhou. Centroid Prior Topic Model for Multi-label Classification. Pattern Recognition Letters, 2015, 62(1):8-13. SCI, CCF Rank C[26] Ximing Li, Jihong Ouyang and You Lu. Topic Modeling for Large Scale Text Data. Frontiers of Information Technology & Electronic Engineering. 2015, 16(6): 457-465. SCI学术会议PC Member，审稿人 IJCAI 2020, 2021; CVPR 2020, 2021, 2022; ICCV 2021; SIGIR 2021;  AAAI 2019, 2022; CIKM 2019, 2020, 2021;  COLING 2018;  NIPS 2016; KSEM 2018, 2019, 2020, 2021期刊审稿人 ACM Transactions on Information Systems (TOIS)IEEE Transactions on Knowledge and Data Engineering (TKDE)IEEE Transactions on Neural Networks and Learning Systems (TNNLS)Machine Learning JournalInformation SciencesInformation FusionKnowledge-based SystemsNeurocomputingApplied IntelligenceExpert Systems with Applications  教育经历 [1] 2011.9 -- 2015.6 吉林大学       计算机软件 [2] 2008.9 -- 2011.6 吉林大学       计算机软件 [3] 2004.9 -- 2008.6 大连理工大学       计算机软件 工作经历 [1] 2018.9 -- 至今 计算机科学与技术学院      副教授 [2] 2015.7 -- 2018.9 计算机科学与技术学院      讲师 研究方向 [1] 人工智能 [2] 机器学习 [3] 自然语言处理 教师其他联系方式 [1] 电话 : 13944834897 [2] 邮箱 : liximing86@gmail.com；   ximingli@jlu.edu.cn