田英杰助理主任

男,研究员,博士生导师

任职情况:中国科学院大数据挖掘与知识管理重点实验室主任助理

研究方向:最优化与数据挖掘,大数据,智能知识管理,支持向量机,机器学习

工作经历:

2012.6至今    中国科学院大学, 中国科学院虚拟经济与数据科学研究中心,研究员;

2006.62012.6中国科学院大学, 中国科学院虚拟经济与数据科学研究中心,副研究员;

2005.62006.6中国科学院大学, 中国科学院虚拟经济与数据科学研究中心,助理研究员;

1997.42002.9中国人民解放军总参某研究所,助理研究员

教育经历:

2002.92005.6 中国农业大学,经济管理学院,管理学博士;

1994.91997.4 北京理工大学,应用数学系,  理学硕士;

1990.91994.7 山东师范大学,数学系,      理学学士;

获奖情况:

2010 北京市科技进步三等奖, 多目标规划数据挖掘理论、方法及在重要行业中的应用, 排名3, 编号: 2010 -3-004-03.

2011 北京市科技进步二等奖, 最优化信用评分体系与应用, 排名3, 编号: 2011 -2-002-03.

2009 四川省科技进步二等奖,基于数据科学的业银行信用评分理论与系统研究, 排名6, 编号: 2009-2-0346.

5年发表的文章:

专著

[1]      Naiyang Deng, Yingjie Tian, and Chunhua Zhang, Support vector machines: optimization based theory, algorithms, and extensions. CRC Press, 2012. ISBN 978-1-4398-5792-2, pp. 1-335 (2012)

[2]      Yong Shi, Yingjie Tian, Gang Kou, Yi Peng, and Jianping Li, Optimization Based Data Mining: Theory and Applications. Springer, ISBN 978-0-85729-503-3, pp. 1-316 (2011)

[3]      Yong Shi, Lingling Zhang, Yingjie Tian, and Xingsen Li, Intelligent Knowledge—A study beyond Data Mining. Springer, ISBN 978-3-662-46192-1, pp. 1-150 (2014)

期刊

[1]      Yingjie Tian, Zhiquan Qi, Xuchan Ju, Yong Shi, Xiaohui Liu: Nonparallel Support Vector Machines for Pattern Classification. IEEE Transaction on Cybernetics 44(7): 1067-1079 (2014)

[2]      Yingjie Tian, and Ping Yuan, Large-scale linear nonparallel support vector machine solver. Neural Networks,  50: 166-174 (2014).

[3]      Yingjie Tian, Xuchan Ju, Zhiquan Qi,Yong Shi, Improved Twin Support Vector Machine. Science in China Series A: Mathematics,  57(2): 417-432 (2014).

[4]      Yingjie Tian, Zhiquan Qi, Review on: Twin Support Vector Machines, Annals of Data Science, 1(2):253–277(2014).

[5]      Yingjie Tian, Qin Zhang, Yuan Ping: Large-scale linear nonparallel support vector machine solver. Neurocomputing 138: 114-119 (2014)

[6]      Yingjie Tian, Xuchan Ju, Zhiquan Qi: Efficient sparse nonparallel support vector machines for classification. Neural Computing and Applications 24(5): 1089-1099 (2014)

[7]      Yingjie Tian, Xuchan Ju, Zhiquan Qi, Yong Shi: Efficient sparse least squares support vector machines for pattern classification. Computers & Mathematics with Applications 66(10): 1935-1947 (2013)

[8]      Yingjie Tian, Qin Zhang, Dalian Liu, v-Nonparallel support vector machine for pattern classification, Neural Computing and Applications, 25: 1007-1020(2014).

[9]      Yingjie Tian, Yong Shi, and Xiaohui Liu, Recent advances on support vector machines research. Technological and Economic Development of Economy , 18(1): 5-33 (2012).

[10]   Zhiquan Qi, Yingjie Tian*, Yong Shi: Robust twin support vector machine for pattern classification. Pattern Recognition 46(1): 305-316 (2013)

[11]   Zhiquan Qi, Yingjie Tian*, Yong Shi, Successive Overrelaxation for Laplacian Support Vector Machine. IEEE Transactions on Neural Networks and Learning Systems, DOI: 10.1109/TNNLS.2014.2320738 (2014).

[12]   Zhiquan Qi , Yingjie Tian*, and Yong Shi, A nonparallel support vector machine for a classification problem with universum learning, Journal of Computational and Applied Mathematics, 263: 288-298 (2014).

[13]   Zhiquan Qi , Yingjie Tian*, and Yong. Shi, A new classification model using privileged information and its application, Neurocomputing, 129: 146-152 (2014).

[14]   Zhiquan Qi , Yingjie. Tian*, Xiaodan Yu, and Yong Shi, A multi-instance learning algorithm based on nonparallel classifier, Applied Mathematics and Computation, 241: p. 233-241 (2014).

[15]   Zhiquan Qi, Yingjie Tian*, Yong Shi: Regularized multiple-criteria linear programming with universum and its application. Neural Computing and Applications 24(3-4): 621-628 (2014)

[16]   Dalian Liu, Yingjie Tian*, Rongfang Bie, Yong Shi: Self-Universum support vector machine. Personal and Ubiquitous Computing 18(8): 1813-1819 (2014)

[17]   Zhiquan Qi, Yingjie Tian*, Yong Shi: Structural twin support vector machine for classification. Knowledge-Based Systems, 43: 74-81 (2013)

[18]   Zhiquan Qi, Yingjie Tian*, Yong Shi: Efficient railway tracks detection and turnouts recognition method using HOG features. Neural Computing and Applications 23(1): 245-254 (2013)

[19]   Zhiquan Qi, Yingjie Tian*, Yong Shi: Multi-instance classification based on regularized multiple criteria linear programming. Neural Computing and Applications 23(3-4): 857-863 (2013)

[20]   Zhiquan Qi, Yingjie Tian*, Yong Shi: Laplacian twin support vector machine for semi-supervised classification. Neural Networks 35: 46-53 (2012)

[21]   Zhiquan Qi, Yingjie Tian*, Yong Shi: Twin support vector machine with Universum data. Neural Networks 36: 112-119 (2012)

[22]   Ruoying Chen, Wenjing Chen, Sixiao Yang, Di Wu, Yong Wang, Yingjie Tian*, Yong Shi: Rigorous assessment and integration of the sequence and structure based features to predict hot spots. BMC Bioinformatics 12: 311 (2011)

[23]  Dongling Zhang, Yingjie Tian*, Yong Shi: A group of knowledge incorporated multiple criteria linear programming classifiers. Journal. Computational Applied Mathematics 235(13): 3705-3717 (2011)