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教授

李熙铭

基本信息




姓名:李熙铭

职称:教授(菠菜导航网唐敖庆青年学者)

院系:菠菜导航

办公地点: 计算机楼B527

联系方式: (+86)13944834897

       liximing86@gmail.com

        ximingli@jlu.edu.cn


主要研究领域为人工智能、机器学习(弱监督学习)、自然语言处理。承担国自然面上项目、青年项目、企业技术开发项目、博士后面上项目、吉林省博士后择优资助项目等; 作为骨干成员参与科技部新一代人工智能2030重大项目,国自然区域联合重点基金、省部级重点研发项目等科研项目10余项。累计发表学术论文80余篇,包括ICLR, ICML, ACL, WWW, AAAI, IJCAI, SIGIR, EMNLP, CIKM, SDM, COLING, ACM TKDD, IEEE 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。




NEWS:

2024/05/02 - One full paper has been accepted by ICML 2024

2024/04/17 - Four full paper has been accepted by IJCAI 2024

2024/04/10 - One full paper has been accepted by Neural Networks

2024/02/01 - One full paper has been accepted by WWW 2024

2023/12/16 - One full paper has been accepted by ACM TKDD

2023/12/09 - Two full paper has been accepted by AAAI 2024

2023/08/05 - One full paper has been accepted by CIKM 2023

2023/05/02 - One full paper has been accepted by ACL 2023

2023/04/25 - One full paper has been accepted by ICML 2023

2023/04/19 - One full paper has been accepted by IJCAI 2023

2023/03/22 - One full paper has been accepted by Information Fusion

2022/11/19 - Three full papers have been accepted by AAAI 2023

2022/11/08 - One full paper has been accepted by IEEE TNNLS

2022/08/16 - One full paper has been accepted by COLING 2022

2022/08/03 - One full paper has been accepted by CIKM 2022

2022/04/21 - One full paper has been accepted by IJCAI-ECAI 2022

2022/04/10 - One full paper has been accepted by KAIS

2022/03/31 - Two full papers have been accepted by SIGIR 2022

2022/01/21 - One full paper has been accepted by ICLR 2022

2022/01/14 - One full paper has been accepted by WWW 2022




代表性论文列表 (* 通讯作者)




会议论文

[1] Changchun Li, Yuanchao Dai, Lei Feng, Ximing Li*, Bing Wang, Jihong Ouyang. Positive and Unlabeled Learning with Controlled Probability Boundary Fence, International Conference on Machine Learning (ICML), 2024, in press. CCF Rank A.

[2] Ximing Li, Yuanchao Dai, Bing Wang, Changchun Li, Renchu Guan, Jihong Ouyang. WPML3CP: Wasserstein Partial Multi-Label Learning with Dual Label Correlation Perspectives, International Joint Conference on Artificial Intelligence (IJCAI), 2024, in press. CCF Rank A.

[3] Shuai Lv, Meng Kang, Ximing Li*. Alleviating Imbalanced Pseudo-label Distribution: Self-Supervised Multi-Source Domain Adaptation with Label-specific Confidence, International Joint Conference on Artificial Intelligence (IJCAI), 2024, in press. CCF Rank A.

[4] Yonghao Liu, Mengyu Li, Di Liang, Ximing Li, Fausto Giunchiglia, Lan Huang, Xiaoyue Feng, Renchu Guan. Resolving Word Vagueness with Scenario-guided Adapter for Natural Language InferenceInternational Joint Conference on Artificial Intelligence (IJCAI), 2024, in press. CCF Rank A.

[5] Rui Sun, Yiyuan Wang, Shimao Wang, Hui Li, Ximing Li, Minhao Yin. Nukplex: An Efficient Local Search Algorithm for Maximum K-Plex ProblemInternational Joint Conference on Artificial Intelligence (IJCAI), 2024, in press. CCF Rank A.

[6] Yonghao Liu, Lan Huang, Bowen Cao, Ximing Li, Fausto Giunchiglia, Xiaoyue Feng, Renchu Guan. A Simple but Effective Approach for Unsupervised Few-Shot Graph ClassificationThe Web Conference (WWW), 2024, in press. CCF Rank A.

[7] Jihong Ouyang, Zhiyao Yang, Silong Liang, Bing Wang, Yimeng Wang, Ximing Li*. Aspect-Based Sentiment Analysis with Explicit Sentiment Augmentations, AAAI Conference on Artificial Intelligence (AAAI), 2024, in press. CCF Rank A.

[8] Jiaan Wang, Jianfeng Qu, Kexin Wang, Zhixu Li, Wen Hua, Ximing Li, An Liu, Improving the Robustness of Knowledge-Grounded Dialogue via Contrastive Learning, AAAI Conference on Artificial Intelligence (AAAI), 2024, in press. CCF Rank A.

[9] Jihong Ouyang, Zhiyao Yang, Chuang Xuan, Bing Wang, Yiyuan Wang, Ximing Li*. Unsupervised Aspect Term Extraction by Integrating Sentence-level Curriculum Learning with Token-level Self-paced Learning, ACM International Conference on Information and Knowledge Management (CIKM), 2023, 1982–1991, CCF Rank B.

[10] Changrong Min, Hongfei Lin, Ximing Li*, Zhilin Wang, Liang Yang, Bo Xu. Just Like a Human Would, Direct Access to Sarcasm Augmented with Potential Result and Reaction. Annual Meeting of the Association for Computational Linguistics (ACL), 2023, 10172–10183. CCF Rank A.

[11] Xin Cheng, Yuzhou Cao, Ximing Li, Bo An, Lei Feng*. Weakly Supervised Regression with Interval Targets. International Conference on Machine Learning (ICML), 2023, 5428-5448. CCF Rank A.

[12] Yonghao Liu, Di Liang, Mengyu Li, Fausto Giunchiglia, Ximing Li, Sirui Wang, Wei Wu, Lan Huang, Xiaoyue Feng*, Rechu Guan*. Local and Global: Temporal Question Answering via Information Fusion. International Joint Conference on Artificial Intelligence (IJCAI), 2023, 5141-5149. CCF Rank A.

[13] Ximing Li, Yuanzhi Jiang, Changchun Li*, Yiyuan Wang, Jihong Ouyang. Learning with Partial Labels from Semi-supervised Perspective. AAAI Conference on Artificial Intelligence (AAAI), 2023, 1501–1536. CCF Rank A.

[14] Bo Cheng, Ximing Li*, Yi Chang*. TC-DWA: Text Clustering with Dual Word-level Augmentation. AAAI Conference on Artificial Intelligence (AAAI), 2023, 7113-7121. CCF Rank A.

[15] Jinjin Chi, Zhiyao Yang, Ximing Li*, Jihong Ouyang, Renchu Guan. Variational Wasserstein Barycenters with c-Cyclical Monotonicity Regularization. AAAI Conference on Artificial Intelligence (AAAI), 2023, 7157-7165. CCF Rank A.

[16] Bing Wang, Liang Ding*, Qihuang Zhong, Ximing Li, Dacheng Tao. A Contrastive Cross-Channel Data Augmentation Framework for Aspect-Based Sentiment Analysis. International Conference on Computational Linguistics (COLING). 2022, 6691-6704. CCF Rank B.

[17] Zhiqi Ge, Yuanyuan Guan, Ximing Li*, Bo Fu. Consistent, Balanced, and Overlapping Label Trees for Extreme Multi-label Learning. ACM International Conference on Information and Knowledge Management (CIKM), 2022, in press, CCF Rank B.

[18] Jihong Ouyang, Yiming Wang, Ximing Li*. Weakly-supervised Text Classification with Wasserstein Barycenters Regularization. International Joint Conference on Artificial Intelligence (IJCAI), 2022, in press. CCF Rank A.

[19] Yonghao Liu, Mengyu Li, Ximing Li, Fausto Giunchiglia, Xiaoyue Feng and Renchu Guan Few-shot Node Classification on Attributed Networks with Graph Meta-learning. SIGIR, 2022, in press. CCF Rank A.

[20] Renchu Guan, Haoyu Pang, Fausto Giunchiglia, Ximing Li, Xuefeng Yang and Xiaoyue Feng Deployable and Continuable Meta-Learning-Based Recommender System with Fast User-Incremental Updates. SIGIR, 2022, in press. CCF Rank A.

[21] Changchun Li, Ximing Li*, Lei Feng, Jihong Ouyang. Who Is Your Right Mixup Partner in Positive and Unlabeled Learning. International Conference on Learning Representations (ICLR) , 2022, in press.

[22] Haoyu Pang, Fausto Giunchiglia, Ximing Li, Renchu Guan and Xiaoyue Feng PNMTA: A Pretrained Network Modulation and Task Adaptation Approach for User Cold-Start Recommendation. The Web Conference (WWW), 2022, in press. CCF Rank A.

[23] 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, 18-27. (Findings) CCF Rank B.

[24] 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, 903-912. CCF Rank B.

[25] 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, 555-564. CCF Rank B.

[26] 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, 617-626. CCF Rank B.

[27] Changchun Li, Ximing Li* and Jihong Ouyang. Semi-Supervised Text Classification with Balanced Deep Representation Distributions. Annual Meeting of the Association for Computational Linguistics and the International Joint Conference on Natural Language Processing (ACL-IJCNLP), 2021, 5044-5053. CCF Rank A.

[28] Yiming Wang, Ximing Li *, Jihong Ouyang. Layer-Assisted Neural Topic Modeling over Document Networks. International Joint Conference on Artificial Intelligence (IJCAI), 2021, 3148-3154. CCF Rank A.

[29] 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.

[30] 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.

[31] 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.

[32] 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.

[33] 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.

[34] 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.

[35] 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.

[36] 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.

[37] 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.

[38] 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.

[39] 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.

[40] 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.

[41] 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.

[42] 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.

[43] 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.

[44] 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] Bing Wang, Ximing Li*, Zhiyao Yang, Yuanyuan Guan, Jiayin Li, Shengsheng Wang*. Unsupervised Sentence Representation Learning with Frequency-induced Adversarial Tuning and Incomplete Sentence Filtering, Neural Networks, 2024, in press, SCI, CCF Rank B

[2] Ximing Li, Bing Wang, Yang Wang, and Meng Wang. Graph-based Text Classification by Contrastive Learning with Text-level Graph Augmentation. ACM Transactions on Discovery from Data, 2024, 14(8), 1-21. SCI, CCF Rank B

[3] Changrong Min, Hongfei Lin, Ximing Li*, He Zhao, Junyu Lu, Liang Yang, Bo Xu. Finding Hate Speech with Auxiliary Emotion Detection from Self-supervised Multi-label Learning Perspective. Information Fusion, 2023, 96, 214-223. SCI, 中科院一区.

[4] Zhiyao Yang, Bing Wang, Ximing Li, Wenting Wang, Jihong Ouyang. S3MAP: Semisupervised Aspect-based Sentiment Analysis with Masked Aspect Prediction. Knowledge-based Systems, 2023, in press. SCI, 中科院二区.

[5] Ouyang Jihong, Zhengjie Zhang, Qingyi Meng, Ximing Li*. Adaptive Prototype and Consistency Alignment for Semi-supervised Domain Adaptation. Multimedia and Application Tools, 2023, in press. SCI, 中科院二区.

[6] Ximing Li, Bing Wang, Yue Wang, Jihong Ouyang. Weakly Supervised Prototype Topic Model with Discriminative Seed Words: Modifying the Category Prior by Self-exploring Supervised Signals. Soft Computing, 2023, in press. SCI, 中科院三区.

[7] Bo Cheng, Ximing Li*, Yi Chang*. Eliminating Negative Word Similarities for Measuring Document Distances: A Thoroughly Empirical Study on Word Movers Distance. IEEE Transactions on Neural Networks and Learning Systems.2022, in press. SCI, CCF Rank B

[8] Ximing Li, Changchun Li, Jinjin Chi, Jihong Ouyang. Approximate Posterior Inference for Bayesian Models: Black-box Expectation Propagation. Knowledge and Information Systems, 2022, in press. SCI, CCF Rank B.

[9] Jinjin Chi, Bilin Wang, Huiling Chen, Lejun Zhang*, Ximing Li*, Jihong Ouyang, Approximate Continuous Optimal Transport with Copulas, International Journal of Intelligent Systems, 2021, in press. SCI, CCF Rank C.

[10] 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.

[11] 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

[12] 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

[13] 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

[14] Zhijuan Xu, Xueyan Liu, Xianjuan Cui, Ximing Li and Bo Yang. Robust Stochastic Block Model. Neurocomputing. 2019, 379:398-412, SCI, CCF Rank C

[15] 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

[16] 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

[17] 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

[18] 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

[19] 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

[20] 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

[21] 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

[22] 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

[23] 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

[24] 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

[25] 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

[26] 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

[27] 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

[28] 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

[29] 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.

[30] Ximing Li, Jihong Ouyang and Xiaotang Zhou. Supervised Topic Models for Multi-label Classification. Neurocomputing, 2015, 149:811-819. SCI, CCF Rank C

[31] 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

[32] 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

[33] 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

[34] 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

[35] 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





学术兼职

Big Data and Cognitive Computing (SCI), 编委


Intelligent Automation & Soft Computing (SCI), Special Issue “Emerging Trends in Intelligent Data Analysis for Sparse, Noisy, and High-Dimensional Data”, Leading Guest Editor.

https://www.techscience.com/iasc/special_detail/sparse-and-noisy





学术会议PC Member

IJCAI 2020, 2021, 2022, 2023; 2024

SIGIR 2021, 2022;

WWW 2021, 2022, 2023, 2024;

ICML 2022, 2023, 2024;

AAAI 2019, 2021, 2022, 2023, 2024;

ACL 2023, 2024;

EMNLP 2023;

CVPR 2020, 2021, 2022, 2023, 2024;

CIKM 2019, 2020, 2021, 2022, 2023, 2024;

WSDM 2023, 2024;

ICCV 2021, 2023;

COLING 2018;

ICME 2021, 2022, 2024;

NeurIPS 2022, 2023, 2024;

DASFAA 2023, 2024;

KSEM 2018, 2019, 2020, 2021, 2022, 2023, 2024




期刊审稿人

ACM Transactions on Information Systems (TOIS)

IEEE Transactions on Pattern Pattern Analysis and Machine Intelligence (TPAMI)

IEEE Transactions on Knowledge and Data Engineering (TKDE)

IEEE Transactions on Neural Networks and Learning Systems (TNNLS)

Machine Learning Journal

Computer Journal

Neural Networks

Information Sciences

Information Fusion

Knowledge-based Systems

Neurocomputing

Applied Intelligence

Expert Systems with Applications