Ying-Jie Tian
Ying-Jie Tian
Chinese Academy of Sciences
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支持向量机: 理论、算法与拓展
邓乃扬, 田英杰
科学出版社, 2009
A comprehensive survey of clustering algorithms
D Xu, Y Tian
Annals of data science 2, 165-193, 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
Robust twin support vector machine for pattern classification
Z Qi, Y Tian, Y Shi
Pattern recognition 46 (1), 305-316, 2013
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
Optimization Based Data Mining: Theory and Applications
Y Shi, Y Tian, G Kou, Y Peng, J Li
Springer, 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
Laplacian twin support vector machine for semi-supervised classification
Z Qi, Y Tian, Y Shi
Neural networks 35, 46-53, 2012
Recent advances on support vector machines research
Y Tian, Y Shi, X Liu
Technological and economic development of Economy 18 (1), 5-33, 2012
Structural twin support vector machine for classification
Z Qi, Y Tian, Y Shi
Knowledge-based systems 43, 74-81, 2013
Twin support vector machine with universum data
Z Qi, Y Tian, Y Shi
Neural Networks 36, 112-119, 2012
A comprehensive survey on regularization strategies in machine learning
Y Tian, Y Zhang
Information Fusion 80, 146-166, 2022
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
Support vector machine classifier with truncated pinball loss
X Shen, L Niu, Z Qi, Y Tian
Pattern Recognition 68, 199-210, 2017
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
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
Survey and experimental study on metric learning methods
D Li, Y Tian
Neural networks 105, 447-462, 2018
Predicting DNA-and RNA-binding proteins from sequences with kernel methods
X Shao, Y Tian, L Wu, Y Wang, L Jing, N Deng
Journal of theoretical biology 258 (2), 289-293, 2009
When ensemble learning meets deep learning: a new deep support vector machine for classification
Z Qi, B Wang, Y Tian, P Zhang
Knowledge-Based Systems 107, 54-60, 2016
Unsupervised feature learning from time series.
Q Zhang, J Wu, H Yang, Y Tian, C Zhang
IJCAI, 2322-2328, 2016
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