Profile:

Ximing Li received his Ph.D (2015) from Jilin University. He joined Jilin University in 2015 and became an Associate Professor in 2018. His research intersets include Artificial Intelligence, Machine Learning and Natural Language Processing. He has published more than 40 papers at the competitive venues and journals, including AAAI, ACL, WWW, IJCAI, CIKM, SDM, COLING, TNNLS, Machine Learning, KAIS, etc.

2021/10/01 - One full paper has been accepted by WWW  Journal

2021/08/26 - One full paper has been accepted by EMNLP

2021/08/08 - 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 

Publication List ( * Corresponding Author)

Conference Paper

[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.

Journal Paper

       [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

Conference PC Members

IJCAI2020, 2021;

CVPR2020, 2021, 2022;

ICCV2021;

SIGIR2021;  

AAAI2019, 2022;

CIKM2019, 2020, 2021;  

COLING2018;  

NIPS2016;

KSEM2018, 2019, 2020, 2021

Journal Reviewers

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 Journal

Information Sciences

Information Fusion

Knowledge-based Systems

Neurocomputing

Applied Intelligence

Expert Systems with Applications