周博 讲 师


工作地点：财经主楼 613#


邮 箱：bozhou@xjtu.edu.cn

教育经历：

2003.9-2007.7 南京大学，软件工程学士学位。
2007.9-2009.9 日本早稻田大学, IPS（Information, Production and system）大学院，信息方向硕士学位。
2009.9-2018.9 日本早稻田大学, IPS（Information, Production and system）大学院, 工学博士学位。
主要研究课题：
? 支持向量机（SVM）及核方法
? 半监督学习
? 深度学习
机器学习方法在经济学领域的应用


发表论文情况：
杂志论文发表（五篇SCI 检索）：
1.B. Zhou, B. Chen and J. Hu, "Quasi-linear Support Vector Machine for Nonlinear Classification",
IEICE Trans. on Fundamentals of Electronics, Communications and Computer Sciences,Vol.E97-A,
No.7, July, pp.1587-1594, 2014.
2. W. Li,B. Zhou, B. Chen and J. Hu, "A Deep Neural Network Based Quasi-linear Kernel for Support
Vector Machines",IEICE Trans. on Fundamentals of Electronics, Communications and Computer
Sciences,Vol.E99-A, No.12, Dec., 2016.
3. W.Li,B.Zhou, B.Chen and J.Hu, "A Geometry-Based Two-step Method for Nonlinear Classification
Using Quasi-Linear Support Vector Machine",IEEJ Trans. on Electrical and Electronic Engineering,
Vol.12, No.6, Nov., 2017.
4.B.Zhou, W.Li and J.Hu, "A New Segmented Oversampling Method for Imbalanced Data
Classification Using Quasi-Linear Support Vector Machine",IEEJ Trans. on Electrical and
Electronic Engineering,Vol.12, No.6, Nov., 2017.
5. B. Zhou, W. Li and J. Hu, "A Coarse-to-Fine Two-step Method for Semi-Supervised Classification
Using Quasi-Linear Laplacian SVM", submitted toIEEJ Trans. on Electrical and Electronic
Engineering.(Received)
会议论文发表：
1.B. Zhouand J. Hu, "A Dynamic Pattern Recognition Approach Based on Neural Network for Stock
Time-Series", inProc. of World Congress on Nature and Biologically Inspired Computing(NaBIC
2009) (India), 12, 2009, pp.1552-1555.
2.B. Zhou, C. Yang, H. Guo and J. Hu, "A Quasi-linear SVM Combined with Assembled SMOTE for
Imbalanced Data Classification", inProc. of 2013 IEEE International Joint Conference on Neural
Networks(IJCNN'2013) (Dallas), Aug., 2013, pp.2351-2357.
3. C. Hu,B. Zhou, and J. Hu, "Fast Support Vector Data Description Training Using Edge Detection
on Large Datasets", inProc. of 2014 IEEE International Joint Conference on Neural Networks
(IJCNN'2014) (Beijing), July, 2014, pp.2176-2182.(Best Student Paper Award - Finalist)
4.B. Zhou, C. Hu, B. Chen and J. Hu, "A Transductive Support Vector Machine with Adjustable
Quasi-linear Kernel for Semi-supervised Data Classification", inProc. of 2014 IEEE International
Joint Conference on Neural Networks(IJCNN'2014) (Beijing), July, 2014, pp.1409-1415.
5.B. Zhou, D. Fu, C. Dong and J. Hu, "A Transductive SVM with Quasi-linear Kernel Based on
Cluster Assumption for Semi-Supervised Classification", inProc. of 2015 IEEE International Joint
Conference on Neural Networks(IJCNN'2015) (Killarney), July, 2015.
6. D. Fu,B. Zhouand J. Hu, "Improving SVM Based Multi-label Classification by Using Label
Relationship", inProc. of 2015 IEEE International Joint Conference on Neural Networks
(IJCNN'2015) (Killarney), July, 2015.
7. C. Dong,B. Zhouand J. Hu, "A Hierarchical SVM Based Multiclass Classification by Using
Similarity Clustering", inProc. of 2015 IEEE International Joint Conference on Neural Networks
(IJCNN'2015) (Killarney), July, 2015.
8. W. Li,B. Zhouand J. Hu, "A Kernel Level Composition of Multiple Local Classifiers for Nonlinear
Classification", in Proc. of 2016 IEEE International Joint Conference on Neural Networks
(IJCNN'2016) (Vancouver), July, 2016, pp.3845-3850.
9. W. Li, B. Chen,B. Zhou, & J. Hu. A mixture of multiple linear classifiers with sample weight and
manifold regularization. In Proc. of 2017 IEEE International Joint Conference on Neural Networks
(IJCNN'2017), May, 2017. pp. 3747-3752.


项目经历及获奖情况：
1. 参与了国家自然科学青年基金项目“石油储层识别中软计算与硬计算融合的理论与方法研究”的研究工
作（项目编码：**， 主持人：郭海湘）。研究成果发表于2013 年国际神经网络大会，B. Zhou,
C. Yang, H. Guo and J. Hu, "A Quasi-linear SVM Combined with Assembled SMOTE for Imbalanced
Data Classification"。
2. 论文C. Hu, B. Zhou, and J. Hu, "Fast Support Vector Data Description Training Using Edge
Detection on Large Datasets" 获得2014 年国际神经网络大会最佳学生论文奖提名（大会共提名两篇）。