Basic Information

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Contact

School of Mathematics and Statistics

Xi’an Jiaotong University

Xi’an, Shaanxi Province

China, 710049

Phone Number: +86-029-82663004

E-Mail: cxzhang@mail.xjtu.edu.cn

 

Education Experience

9/2008-9/2009
Visiting Scholar in Pattern Recognition Group, Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology
3/2005-3/2010
Ph.D candidate in Applied Mathematics, School of Science, Xi’an Jiaotong University
9/2002-3/2005
M.S. candidate in Probability & Statistics, School of Science, Xi’an Jiaotong University
9/1998-7/2002
B.S. candidate in Mathematics and Applied mathematics, Department of Mathematics, Xinyang Normal University

Scientific Research

l        Research Field

       Ensemble learning, Stochastic sampling methods, High-dimensional data analysis, Deep learning.

l        Recent Publications

[1]  Chun-Xia Zhang*, Shuang Xu, Jiang-She Zhang. A novel variational Bayesian method for variable selection in logistic regression models. Computational Statistics and Data Analysis, 2019, 133: 1-19.

[2]  Chunxia Zhang*, Yilei Wu, Mu Zhu. Pruning variable selection ensembles. Statistical Analysis and Data Mining, 2019, 12(3): 168-184.

[3] Chun-Xia Zhang*, Sang-Woon Kim, Jiang-She Zhang. On selective learning in stochastic stepwise ensembles. International Journal of Machine Learning and Cybernetics, 2020, 11(1): 217-230.

[4]  Shuang Xu, Chun-Xia Zhang*. Robust sparse regression by modeling noise as a mixture of gaussians. Journal of Applied Statistics, 2019, 46(10): 1738-1755.

[5] Bao Guo, Chunxia Zhang, Junmin Liu*, Xiaoyi Ma. Improving text classification with weighted word embedding via a multi-channel TextCNN model. Neurocomputing, 2019, 363: 366-374.

[6] Wang Guan-wei, Zhang Chun-xia*, Yin Qing-yan. RS-BART: a novel technique to boost the prediction ability of Bayesian additive regression trees. Chinese Journal of Engineering Mathematics, 2019, 36(4): 461-477.

 

Teaching

Undergraduate course  "Data Analysis and Statistical Software",  48 class hours.
Undergraduate course  "Statistical Learning", 32 class hours.

Undergraduate course  "Linear Alebra and Analytic Geometry",  64 class hours.