机器学习  

数据挖掘

最优化 

智能知识管理 
 

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070105-运筹学与控制论
120100-管理科学与工程
081203-计算机应用技术

最优化与数据挖掘
数据挖掘与知识管理
数据挖掘与机器学习

2012-06--至今          中国科学院大学 研究员

2006-06--2012-06    中国科学院大学 副研究员

2005-06--2006-06    中国科学院大学 助理研究员

1997-04--2002-09    中国人民解放军某研究所 助理研究员 

专著：

1. 田英杰, 唐静静, 机器学习与最优化. 科学出版社, 北京, 2024.

2. 付赛际, 田英杰, 医疗大数据与机器学习. 清华大学出版社, 北京, 2023.

3.   Naiyang Deng, Yingjie Tian, Chunhua Zhang , Support vector machines: optimization based theory, algorithms, and extensions, CRC Press, 2012

4.   Yong Shi，Yingjie Tian，Gang Kou，Yi Peng，Jianping Li ，Optimization Based Data Mining: Theory and Applications，Springer，2011

5. 邓乃扬, 田英杰, 支持向量机理论、算法与拓展. 科学出版社, 北京, 2009.

6. 邓乃扬, 田英杰, 数据挖掘中的新方法: 支持向量机.  科学出版社, 北京, 2004.

近5年代表性论文（*为通讯作者）：

1. Shaokai Xu, Muyang Li, Yingjie Tian*, Bidirectional gradient optimization for graph knowledge distillation: Reactivating KL divergence via component decoupling, Information Sciences, 2026, 741: 123299.

2. Xiaoxiao Wang, Yingjie Tian*, Towards provenance-aware diffusion:Key-free watermarking with Gaussian shading, Expert Systems With Applications, 2026, 306: 130822.

3. Yingjie Tian, Xiaoxiao Wang, Watermarking via Gaussian noise modulation in diffusion models, Neurocomputing, 2026, 665: 132188.

4. Haonan Wen, Yingjie Tian*, Kun Guo, Estimating undisclosed corporate greenhouse gas emissions using energy consumption data as privileged information, International Review of Financial Analysis, 2026, 110:104987.

5. Yingjie Tian, Minghao Liu, Haoran Jiang, et al., SketchRefiner: Text-Guided Sketch Refinement Through Latent Diffusion Models, IEEE Transactions on Visualization and Computer Graphics, 2025, 31(12): 10711~10722.

6. Minghao Liu, Le Zhang, Yingjie Tian*, Xiaochao Qu, Luoqi Liu, Ting Liu, Draw Like an Artist: Complex Scene Generation with Diffusion Model via Composition, Painting, and Retouching, IEEE Transactions on Circuits and Systems for Video Technology,  2025,DOI 10.1109/TCSVT.2025.3626857

7. Yingjie Tian, Minghao Liu, Duo Su, Cliprefiner: Enhancing Realism and Detail in Free-Hand Sketches Through Semantically-Aware Optimization, Pattern Recognition Letters, 2025, 198: 64–70.

8. Yingjie Tian, Haonan Wen, Kun Guo, Machine learning applications in climate finance: An overview,  Research in International Business and Finance, 2025, 79: 103063.  

9. Jianyu Miao, Xiaochan Zhang, Tiejun Yang,  Chao Fan,  Yingjie Tian,  Yong Shi, Mingliang Xu,  A Comprehensive Survey on Subspace Clustering: Methods and Applications,  Artificial Intelligence Review, 2025, 58: 346.

10. Saiji Fu, Haonan Wen, Xiaoxiao Wang, Yingjie Tian*, Self-improved multi-view interactive knowledge transfer, Information Fusion, 2025, 114: 102718.

11. Yingjie Tian, Haoran Jiang, Recent advances in complementary label learning, Information Fusion, 2025, 114: 102702.

12. Yingjie Tian, Siyu Zhao, Xingyu Zhang, Robustness and orthogonality: Time series forecasting via wavelets, Information Sciences, 2025, 717:122328. 

13. Yingjie Tian, Shaokai Xu, Muyang Li, Class-view graph knowledge distillation: A new idea for learning MLPs on graphs, Neurocomputing, 2025, 637: 130035.

14. Xiaotong Yu, Shiding Sun, Yingjie Tian*, Sample selection for noisy partial label learning with interactive contrastive learning, Pattern Recognition, 2025, 166: 111681.

15. Xiaoxi Zhao, Yingjie Tian, Chonghua Zheng, Robust one-class support vector machine, Neural Networks, 2025, 188: 107416.

16. Long Tang, Pengfei Yan, Yingjie Tian, Pano.M. Pardalos, Self-adaptive label discovery and multi-view fusion for complementary label learning, Neural Networks, 2025, 181: 106763.

17. Long Tang, Yelei Liu, Yingjie Tian, Panos M Pardalos, Complementary label learning with multi-view data and a semi-supervised labeling mechanism, Pattern Recognition, 2025, 165: 111651.

18. Jianyu Miao, Jingjing Zhao, Tiejun Yang, Yingjie Tian, Yong Shi, Mingliang Xu, Robust sparse orthogonal basis clustering for unsupervised feature selection, Expert Systems With Applications, 2025, 274:126890.

19. Yingjie Tian, Haonan Wen, Saiji Fu∗, Multi-step ahead prediction of carbon price movement using time-series privileged information, Expert Systems With Applications, 2024, 255:124825.

20. Jingjing Tang, Yan Li, Zhaojie Hou, Saiji Fu, Yingjie Tian*, Robust two-stage instance-level cost-sensitive learning method for class imbalance problem Knowledge-Based Systems, 2024, 300:112143.

21. Yingjie Tian, Shaokai Xu, Muyang Li, Decoupled graph knowledge distillation: A general logits-based method for learning MLPs on graphs, Neural Networks, 2024, 179:106567.

22. Zhaojie Hou, Jingjing Tang, Yan Li, Saiji Fu, Yingjie Tian, MVQS: Robust multi-view instance-level cost-sensitive learning method for imbalanced data classification, Information Sciences, 2024, 675: 120467.

23. Jingjing Tang, Bangxin Liu, Saiji Fu, Yingjie Tian, Gang Kou, Advancing robust regression: Addressing asymmetric noise with the BLINEX loss function, Information Fusion, 2024, 110: 102463.

24. Jingjing Tang, Qingqing Yi, Saiji Fu*, Yingjie Tian, Incomplete multi-view learning: Review, analysis, and prospects, Applied Soft Computing, 2024, 153:111278.

25. Saiji Fu, Tianyi Dong, Zhaoxin Wang, Yingjie Tian*, Weakly privileged learning with knowledge extraction, Pattern Recognition, 2024,153:110517,

26. Shiding Sun, Bo Wang, Yingjie Tian*, Decoupled Representation for Multi-View Learning, Pattern Recognition, 2024, 151:110377.

27. Duo Su, Junjie Hou, Weizhi Gao, Yingjie Tian*, Bowen Tang, D4M: Dataset Distillation via Disentangled Diffusion Model, IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR-2024),  5809~5818.

28. Haoran Jiang, Zhihao Sun, Yingjie Tian*, Navigating Real-World Partial Label Learning: Unveiling Fine-Grained Images with Attributes, the 38th AAAI Conference on Artificial Intelligence (AAAI-2024), 12874~12882. 

29. Dalian Liu, Saiji Fu, Yingjie Tian*, Jingjing Tang, Universum driven cost-sensitive learning method with asymmetric loss function, Engineering Applications of Artificial Intelligence, 2024, 131: 107849.

30. Yingjie Tian, Duo Su, Shilin Li, Adaptive robust loss for landmark detection, Information Fusion, 2024, 101: 102013.

31. Xiaotong Yu, Shiding Sun, Yingjie Tian∗, Self-distillation and Self-supervision for Partial Label Learning, Pattern Recognition, 2024, 146: 110016.

32. Yingjie Tian, Yuhao Xie, Artificial cheerleading in IEO: Marketing campaign or pump and dump scheme,  Information Processing and Management, 2024, 61: 103537.

33. Haoran Jiang, Zhihao Sun, Yingjie Tian∗, ComCo: Complementary Supervised Contrastive Learning for Complementary Label Learning, Neural Networks, 2024, 169: 44~56.

34. Saiji Fu, Xiaoxiao Wang, Jingjing Tang, Shulin Lan, Yingjie Tian*, Generalized robust loss functions for machine learning, Neural Networks, 2024，171: 200~214.

35. Kai Li, Jie Yang, Siwei Ma, Bo Wang, Shanshe Wang, Yingjie Tian*, Zhiquan Qi, Rethinking Lightweight Convolutional Neural Networks for Efficient and High-quality Pavement Crack Detection,  IEEE Transactions on Intelligent Transportation Systems, 2024, 25(1):237~250.

36. 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. 

37. Saiji Fu, Duo Su, Shilin Li, Shiding Sun, Yingjie Tian*, Linear-exponential loss incorporated deep learning for imbalanced classification, ISA Transactions, 2023, 140: 279~292.  

38. Saiji Fu, Xiaoxiao Wang, Yingjie Tian*, Tianyi Dong, Jingjing Tang, Jicai Li, Coarse-grained privileged learning for classification,  Information Processing and Management, 2023, 60: 103506.

39. Yingjie Tian, Kunlong Bai, End-to-End multitask learning with vision transformer,  IEEE Transactions on Neural Networks and Learning Systems, 2024, 35(7): 9579~9590.

40. Yingjie Tian, Kunlong Bai, Xiaotong Yu, and Siyu Zhu, Causal Multi-Label Learning for Image Classification，Neural Networks, 2023, 167: 626~637.

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

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

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

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

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

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

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

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

49. 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.

50. 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.

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

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

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

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

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

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

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

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

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

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

61. 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.