| 支持向量机: 理论、算法与拓展 邓乃扬， 田英杰 科学出版社, 2009 | 2580* | 2009 |
| A comprehensive survey of clustering algorithms D Xu, Y Tian Annals of data science 2, 165-193, 2015 | 2391 | 2015 |
| A comprehensive survey of loss functions in machine learning Q Wang, Y Ma, K Zhao, Y Tian Annals of Data Science, 1-26, 2020 | 817 | 2020 |
| Robust twin support vector machine for pattern classification Z Qi, Y Tian, Y Shi Pattern recognition 46 (1), 305-316, 2013 | 361 | 2013 |
| Optimization Based Data Mining: Theory and Applications Y Shi, Y Tian, G Kou, Y Peng, J Li Springer, 2011 | 319 | 2011 |
| Credit card churn forecasting by logistic regression and decision tree G Nie, W Rowe, L Zhang, Y Tian, Y Shi Expert Systems with Applications 38 (12), 15273-15285, 2011 | 316 | 2011 |
| Nonparallel support vector machines for pattern classification Y Tian, Z Qi, X Ju, Y Shi, X Liu IEEE transactions on cybernetics 44 (7), 1067-1079, 2013 | 279 | 2013 |
| A comprehensive survey on regularization strategies in machine learning Y Tian, Y Zhang Information Fusion 80, 146-166, 2022 | 253 | 2022 |
| Recent advances on support vector machines research Y Tian, Y Shi, X Liu Technological and economic development of Economy 18 (1), 5-33, 2012 | 225 | 2012 |
| Laplacian twin support vector machine for semi-supervised classification Z Qi, Y Tian, Y Shi Neural networks 35, 46-53, 2012 | 223 | 2012 |
| Structural twin support vector machine for classification Z Qi, Y Tian, Y Shi Knowledge-based systems 43, 74-81, 2013 | 162 | 2013 |
| Twin support vector machine with universum data Z Qi, Y Tian, Y Shi Neural Networks 36, 112-119, 2012 | 150 | 2012 |
| Multiview privileged support vector machines J Tang, Y Tian, P Zhang, X Liu IEEE transactions on neural networks and learning systems 29 (8), 3463-3477, 2017 | 126 | 2017 |
| Support vector machine classifier with truncated pinball loss X Shen, L Niu, Z Qi, Y Tian Pattern Recognition 68, 199-210, 2017 | 126 | 2017 |
| Recent advances in stochastic gradient descent in deep learning Y Tian, Y Zhang, H Zhang Mathematics 11 (3), 682, 2023 | 119 | 2023 |
| Recent advances on loss functions in deep learning for computer vision Y Tian, D Su, S Lauria, X Liu Neurocomputing 497, 129-158, 2022 | 113 | 2022 |
| Ramp loss one-class support vector machine; a robust and effective approach to anomaly detection problems Y Tian, M Mirzabagheri, SMH Bamakan, H Wang, Q Qu Neurocomputing 310, 223-235, 2018 | 113 | 2018 |
| Joint ranking SVM and binary relevance with robust low-rank learning for multi-label classification G Wu, R Zheng, Y Tian, D Liu Neural Networks 122, 24-39, 2020 | 110 | 2020 |
| Survey and experimental study on metric learning methods D Li, Y Tian Neural networks 105, 447-462, 2018 | 99 | 2018 |
| Meta-learning approaches for learning-to-learn in deep learning: A survey Y Tian, X Zhao, W Huang Neurocomputing 494, 203-223, 2022 | 92 | 2022 |
Yong ShiProfessor, University of Chinese Academy of Sciences在 ucas.ac.cn 的电子邮件经过验证