Welcome to Yingjie Tian‘s Home Page

Welcome to Yingjie Tian‘s Homepage


Yingjie Tian
Professor
School of Economics and Management, 
UCAS

Research Center on Fictitious Economy and Data Science, CAS


Contact Information
Room 215, Buliding 6
Zhongguancun East Road 80
Haidian District, Beijing
Postcode: 100190
Email: tyj@ucas.ac.cn

Research Areas

Machine learning

Data Mining

Optimization

Intelligent Knowledge Management


Education

2002-09--2005-06 China Agricultural University, Ph.D. 
1994-09--1997-04 Beijing Institute of Technology, M.Sc. 
1990-09--1994-07 Shandong Normal University , B.Sc.

Publications

   
Monographs
1. Naiyang Deng, Yingjie Tian. “New method in Data Mining: Support Vector Machines ” Science Press, 2004,6 Beijing China. 

2. Naiyang Deng, Yingjie Tian. “Support Vector Machines --- Theory, Algorithms and Extensions:” Science Press, 2009,8 Beijing China. 

3. Yong Shi, Yingjie Tian, et al. "Optimization Based Data Mining: Theory and Applications", Springer Press, 2011,5. 

4. Naiyang Deng, Yingjie Tian, Chunhua Zhang. "Support Vector Machines---Optimiaztion based Theory, Algorithms and Extensions", CRC Press, 2012,12.
Selected Papers

1. Saiji Fu, Yingjie Tian*, Long Tang, Robust regression under the general framework of bounded loss functions,  European Journal of Operational Research, 2023, 310: 1325~1339. 

2. Saiji Fu, Duo Su, Shilin Li, Shiding Sun, Yingjie Tian*, Linear-exponential loss incorporated deep learning for imbalanced classification, ISA Transactions, 2023, DOI: https://doi.org/10.1016/j.isatra.2023.06.016

3.   Yingjie Tian, Kunlong Bai, End-to-End multitask learning with vision transformer,  IEEE Transactions on Neural Networks and Learning Systems, 2023, DOI: 10.1109/TNNLS.2023.3234166

4.   Shiding Sun, Xiaotong Yu,  Yingjie Tian*, Multi-view prototype-based disambiguation for partial label learning, Pattern Recognition, 2023, 141: 109625.

5.   Yingjie Tian, Xiaotong Yu, Saiji Fu, Partial label learning: taxonomy, analysis and outlook, Neural Networks, 2023, 161: 708~734.

6.  Yuqi Zhang, Yingjie Tian*, Junjie Hou. CSAST: content self-supervised  and style contrastive learning for arbitrary style transfer, Neural Networks, 2023, 164: 146~155.

7.   Yingjie Tian, Xiaoxi Zhao, Saiji Fu*, Kernel methods with asymmetric and robust loss function,  Expert Systems With Applications, 2023,  213: 119236.

8.   Siyu Zhu,  Yingjie Tian*, Shape robustness in style enhanced cross domain semantic segmentation, Pattern Recognition, 2023, 135: 109143.

9.   Saiji Fu, Yingjie Tian*, Jingjing Tang, Xiaohui Liu, Cost-sensitive learning with modified stein loss function, Neurocomputing, 2023, 525: 57~75.

10.    Yingjie Tian, Yuhao Xie, Picture For Proof (PFPs): aesthetics, IP and post launch performance,  Finance Research Letters, 2023, 55, 103974.

11.   Yingjie Tian, Xiaotong Yu, Saiji Fu*,  Multi-view side information-incorporated tensor completion, Numerical Linear Algebra with Applications, 2023, DOI: 10.1002/nla.2485.

12.   Shiding Sun, Yingjie Tian, Zhiquan Qi, Yang Wu, Weizhi Gao, Yahe Wu, Two-stage training strategy combined with neural network for segmentation of internal mammary artery graft, Biomedical Signal Processing and Control, 2023, 80:104278.

13.   Kai Li, Bo Wang, Yingjie Tian*, Zhiquan Qi. Fast and accurateroad crack detection based on adaptive cost-sensitive loss function, IEEE Transactions on Cybernetics, 2023, 53(2): 1051~1062.

14.   Xiang Gao, Yuqi Zhang, Yingjie Tian*, Learning to incorporate texture saliency adaptive attention to image cartoonizationICML, 2022, 162: 7183~7207.

15.   Yingjie Tian, Yuqi Zhang, A comprehensive survey on regularization strategies in machine  learning,  Information Fusion, 2022, 80: 146~166.

16.   Yingjie Tian, Duo Su, Stanislao Lauria, Xiaohui Liu,  Recent advances on loss functions in deep learning for computer vision, Neurocomputing, 2022, 497: 129~158.

17.   Saiji Fu, Xiaotong Yu, Yingjie Tian*, Cost sensitive ν-support vector machine with LINEX loss,  Information Processing and Management,  2022,  59(2): 102809.

18.   Yingjie Tian, Shiding Sun, Jingjing Tang, Multi-view teacher–student network,  Neural Network, 2022, 146: 69~84.

19.   Jingjing Tang, Dewei Li, Yingjie Tian*, Image classification with multi-view multi-instance metric learning, Expert Systems With Applications, 2022, 189, 116117.

20.   Yingjie Tian, Siyu Zhu, Partial domain adaptation on semantic segmentation, IEEE Transactions on Circuits and Systems for Video Technology,  2022, 32(6): 3798~3809.

21.   Xiang Gao, Yingjie Tian*, Zhiquan Qi, Multi-view feature augmentation with adaptive class activation mapping, IJCAI, 2021, 678-684.

22.   Jiabin Liu, Bo Wang, Xin Shen, Zhiquan Qi, Yingjie Tian, Two-stage training for learning from label proportions,  IJCAI, 2021, 2737-2743.

23.   Yingjie Tian, Saiji Fu, Jingjing Tang, Incomplete-view oriented kernel learning method with generalization error bound, Information Sciences, 2021, 581: 951~977.

24.   Fenfen Zhou, Yingjie Tian*, Zhiquan Qi, Attention transfer network for nature image matting,   IEEE Transactions on Circuits and Systems for Video Technology, 2021, 31(6): 2192~2205.

25.   Xiang Gao, Yingjie Tian*, Zhiquan Qi, RPD-GAN: Learning to draw realistic paintings with generative adversarial network, IEEE Transactions on Image Processing, 2020, 29: 8706~8720.

26.   Yingjie Tian, Mahboubeh Mirzabagheri, Peyman Tirandazic, Seyed Mojtaba Hosseini Bamakan, A non-convex semi-supervised approach to opinion spam detection by ramp-one class SVM, Information Processing and Management, 2020, 57(6): 102381.

27.   Yingjie Tian, Saiji Fu, A descriptive framework for the field of deep learning applications in medical imagesKnowledge-Based Systems, 2020, 210: 106445.

28.   Jiabin Liu, Bo Wang, Zhiquan Qi, Yingjie Tian, Yong Shi, Learning from label proportions with generative adversarial networks, NeurIPS, 2019, 7167~7177.

29.   Jingjing Tang, Yingjie Tian*, Dalian Liu, Gang Kou, Coupling privileged kernel method for multi-view learning, Information Sciences, 2019, 481: 110~127.

30.   Wen Long, Linqiu Song, Yingjie Tian*, A new graphic kernel method of stock price trend prediction based on financial news semantic and structural similarity, Expert Systems With Applications, 2019, 118: 411~424.

31.   Jingjing Tang, Yingjie Tian*, Peng Zhang, and Xiaohui Liu, Multiview privileged support vector machines, IEEE Transactions on Neural Nnetworks and Learning Systems, 2018, 29(8): 3463~3477.

32.   Zhiquan Qi, Fan Meng, Yingjie Tian*, Lingfeng Niu, Yong Shi, and Peng Zhang, Adaboost-LLP: A boosting method for learning with label proportions, IEEE Transactions on Neural Nnetworks and Learning Systems, 2018, 29(8): 3548~3559.

33.   Dewei Li, Yingjie Tian*, Survey and experimental study on metric learning methods, Neural Networks, 2018, 105: 447~462.

34.   Lingfeng Niu, Ruizhi Zhou, Yingjie Tian*, Zhiquan Qi, Peng Zhang, Nonsmooth penalized clustering via lp regularized sparse regression, IEEE Transactions on Cybernetics, 2017, 47(6): 1423~1433.

35.   Huadong Wang, Yong Shi, Lingfeng Niu, and Yingjie Tian, Nonparallel support vector ordinal regression, IEEE Transactions on Neural Nnetworks and Learning Systems, 2017, 47(10): 3306~3317.

36.   Dongkuan Xu, Jia Wu, Dewei Li, Yingjie Tian*, Xingquan Zhu, Xindong Wu, SALE: Self-adaptive LSH encoding for multi-instance learning, Pattern Recognition,  2017, 71: 460~482,

37.   Qin Zhang, Jia Wu, Hong Yang, Yingjie Tian*, Chengqi Zhang, Unsupervised feature learning from time series,  IJCAI, 2016, 2322~2328.

38.   Dandan Chen, Yingjie Tian*, Xiaohui Liu, Structural nonparallel support vector machine for pattern recognition, Pattern Recognition, 2016, 60: 296~305.

39.   Zhiquan Qi, Yingjie Tian*, Yong Shi, Successive Overrelaxation for laplacian support vector machine, IEEE Transactions on Neural Networks, 2015, 26(4): 674~683.

40.   Yingjie Tian, Zhiquan Qi, Xuchan Ju, Yong Shi, Xiaohui Liu, Nonparallel support vector machines for pattern classification, IEEE Transactions on Cybernetics, 2014, 44(7): 1067~1079.