田英杰 男 研究员 博导
经济与管理学院 副院长
中国科学院虚拟经济与数据科学研究中心 副主任
中国科学院大数据挖掘与知识管理重点实验室 副主任
通信地址:北京市海淀区中关村东路80号青年公寓6-202
邮政编码:100190
电子邮件:tyj@ucas.ac.cn
研究领域
机器学习
数据挖掘
最优化
智能知识管理
招生信息
招生专业
招生方向
教育背景
工作经历
2012-06--至今 中国科学院虚拟经济与数据科学研究中心 研究员
2006-06--2012-06 中国科学院虚拟经济与数据科学研究中心 副研究员
2005-06--2006-06 中国科学院虚拟经济与数据科学研究中心 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
专著与论文
专著:
1. Naiyang Deng, Yingjie Tian, Chunhua Zhang , Support vector machines: optimization based theory, algorithms, and extensions, CRC Press, 2012
2. Yong Shi,Yingjie Tian,Gang Kou,Yi Peng,Jianping Li ,Optimization Based Data Mining: Theory and Applications,Springer,2011
3. 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.
4. 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.
5. 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.
6. 田英杰, 唐静静, 机器学习与最优化. 科学出版社, 北京, 2024.
部分论文(*为通讯作者):
1. Saiji Fu, Haonan Wen, Xiaoxiao Wang, Yingjie Tian*, Self-improved multi-view interactive knowledge transfer, Information Fusion, 2025, 114: 102718.
2. Yingjie Tian, Haoran Jiang, Recent advances in complementary label learning, Information Fusion, 2025, 114: 102702.
3. 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.
4. 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.
5. 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.
6. 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.
7. 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.
8. 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.
9. Jingjing Tang, Qingqing Yi, Saiji Fu, Yingjie Tian, Incomplete multi-view learning: Review, analysis, and prospects, Applied Soft Computing, 2024, 153:111278.
10. Saiji Fu, Tianyi Dong, Zhaoxin Wang, Yingjie Tian*, Weakly privileged learning with knowledge extraction, Pattern Recognition, 2024,153:110517,
11. Shiding Sun, Bo Wang, Yingjie Tian*, Decoupled Representation for Multi-View Learning, Pattern Recognition, 2024, 151:110377.
12. 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.
13. 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.
14. 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.
15. Yingjie Tian, Duo Su, Shilin Li, Adaptive robust loss for landmark detection, Information Fusion, 2024, 101: 102013.
16. Xiaotong Yu, Shiding Sun, Yingjie Tian∗, Self-distillation and Self-supervision for Partial Label Learning, Pattern Recognition, 2024, 146: 110016.
17. Yingjie Tian, Yuhao Xie, Artificial cheerleading in IEO: Marketing campaign or pump and dump scheme, Information Processing and Management, 2024, 61: 103537.
18. Haoran Jiang, Zhihao Sun, Yingjie Tian∗, ComCo: Complementary Supervised Contrastive Learning for Complementary Label Learning, Neural Networks, 2024, 169: 44~56.
19. Saiji Fu, Xiaoxiao Wang, Jingjing Tang, Shulin Lan, Yingjie Tian*, Generalized robust loss functions for machine learning, Neural Networks, 2024,171: 200~214.
20. 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.
21. 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.
22. 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.
23. 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.
24. 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.
25. Yingjie Tian, Kunlong Bai, Xiaotong Yu, and Siyu Zhu, Causal Multi-Label Learning for Image Classification,Neural Networks, 2023, 167: 626~637.
26. Shiding Sun, Xiaotong Yu, Yingjie Tian*, Multi-view prototype-based disambiguation for partial label learning, Pattern Recognition, 2023, 141: 109625.
27. Yingjie Tian, Xiaotong Yu, Saiji Fu, Partial label learning: taxonomy, analysis and outlook, Neural Networks, 2023, 161: 708~734.
28. Yuqi Zhang, Yingjie Tian*, Junjie Hou. CSAST: content self-supervised and style contrastive learning for arbitrary style transfer, Neural Networks, 2023, 164: 146~155.
29. Yingjie Tian, Xiaoxi Zhao, Saiji Fu, Kernel methods with asymmetric and robust loss function, Expert Systems With Applications, 2023, 213: 119236.
30. Siyu Zhu, Yingjie Tian*, Shape robustness in style enhanced cross domain semantic segmentation, Pattern Recognition, 2023, 135: 109143.
31. Saiji Fu, Yingjie Tian*, Jingjing Tang, Xiaohui Liu, Cost-sensitive learning with modified stein loss function, Neurocomputing, 2023, 525: 57~75.
32. Yingjie Tian, Yuhao Xie, Picture For Proof (PFPs): aesthetics, IP and post launch performance, Finance Research Letters, 2023, 55, 103974.
33. Yingjie Tian, Xiaotong Yu, Saiji Fu, Multi-view side information-incorporated tensor completion, Numerical Linear Algebra with Applications, 2023, DOI: 10.1002/nla.2485.
34. 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.
35. 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.
36. Xiang Gao, Yuqi Zhang, Yingjie Tian*, Learning to incorporate texture saliency adaptive attention to image cartoonization,ICML, 2022, 162: 7183~7207.
37. Yingjie Tian, Yuqi Zhang, A comprehensive survey on regularization strategies in machine learning, Information Fusion, 2022, 80: 146~166.
38. Yingjie Tian, Duo Su, Stanislao Lauria, Xiaohui Liu, Recent advances on loss functions in deep learning for computer vision, Neurocomputing, 2022, 497: 129~158.
39. Saiji Fu, Xiaotong Yu, Yingjie Tian*, Cost sensitive ν-support vector machine with LINEX loss, Information Processing and Management, 2022, 59(2): 102809.
40. Yingjie Tian, Shiding Sun, Jingjing Tang, Multi-view teacher–student network, Neural Network, 2022, 146: 69~84.
41. Jingjing Tang, Dewei Li, Yingjie Tian*, Image classification with multi-view multi-instance metric learning, Expert Systems With Applications, 2022, 189, 116117.
42. Yingjie Tian, Siyu Zhu, Partial domain adaptation on semantic segmentation, IEEE Transactions on Circuits and Systems for Video Technology, 2022, 32(6): 3798~3809.
43. Xiang Gao, Yingjie Tian*, Zhiquan Qi, Multi-view feature augmentation with adaptive class activation mapping, IJCAI, 2021, 678-684.
44. Jiabin Liu, Bo Wang, Xin Shen, Zhiquan Qi, Yingjie Tian, Two-stage training for learning from label proportions, IJCAI, 2021, 2737-2743.
45. Yingjie Tian, Saiji Fu, Jingjing Tang, Incomplete-view oriented kernel learning method with generalization error bound, Information Sciences, 2021, 581: 951~977.
46. 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.
47. 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.
48. 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.
49. Yingjie Tian, Saiji Fu, A descriptive framework for the field of deep learning applications in medical images,Knowledge-Based Systems, 2020, 210: 106445.
50. Jiabin Liu, Bo Wang, Zhiquan Qi, Yingjie Tian, Yong Shi, Learning from label proportions with generative adversarial networks, NeurIPS, 2019, 7167~7177.
51. Jingjing Tang, Yingjie Tian*, Dalian Liu, Gang Kou, Coupling privileged kernel method for multi-view learning, Information Sciences, 2019, 481: 110~127.
52. 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.
53. 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.
54. 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.
55. Dewei Li, Yingjie Tian*, Survey and experimental study on metric learning methods, Neural Networks, 2018, 105: 447~462.
56. 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.
57. 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.
58. 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,
59. Qin Zhang, Jia Wu, Hong Yang, Yingjie Tian*, Chengqi Zhang, Unsupervised feature learning from time series, IJCAI, 2016, 2322~2328.
60. Dandan Chen, Yingjie Tian*, Xiaohui Liu, Structural nonparallel support vector machine for pattern recognition, Pattern Recognition, 2016, 60: 296~305.
61. Zhiquan Qi, Yingjie Tian*, Yong Shi, Successive Overrelaxation for laplacian support vector machine, IEEE Transactions on Neural Networks, 2015, 26(4): 674~683.
62. 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.
科研活动
科研项目
1、国家自然科学基金面上项目、基于最优化的多视角学习理论、方法与应用研究、在研、主持。
2、****多源异构本底数据融合分析与监测预警研究、在研、主持。
3、国家自然科学基金重点项目、大数据情境下全景式信用理论与演变机制研究、课题、在研、主持。
4、基于大数据的慢性病风险防控服务体系建设、课题、结题、主持。
5、医疗大数据挖掘项目、横向课题、在研、主持。
6、国家自然科学基金面上项目、可拓支持向量机理论、方法与应用研究、结题、主持。
7、国家自然科学基金面上项目、知识驱动的支持向量机理论、算法与应用研究、结题、主持。
8、某部委科技项目、开放网络环境下科技群智汇聚与问题求解系统研究、课题、在研、主持。
9、水利部公益性行业科研专项经费项目、灌区水资源总量控制技术及多维临界调控模式、课题、结题、主持。
10、国家自然科学基金委重大国际(地区)合作项目、最优化数据挖掘的商业智能方法以及在金融与银行管理中的应用、结题、参加。
11、国家自然科学基金青年项目、数据挖掘中的凸规划理论与方法、结题、主持。
12、中国科学院知识创新工程重要方向项目、全球经济监测与政策模拟仿真平台建设预研项目、课题、结题、参加。
13、国家自然科学基金管理学部创新团队、数据挖掘与智能知识管理理论与应用研究、结题、参加。
14、国家自然科学基金重点项目、最优化与数据挖掘、结题、参加。