Projects

  1. 2020年1月-2023年12月, 主要参与人,‘‘充分性降维:最优切片、高维非连续型变量及其应用", 国家自然科学基金面上项目(PI: 王涛).

  2. 2019年12月-2020年11月,主要参与人,‘‘High-dimensional variable selection in network data with nodal information", SJTU-Warwick Joint Seed Fund (PI: Leng Chenlei, 刘卫东).

  3. 2019年9月-2020年9月, 项目负责人,‘‘高维二次型模型的算法研究", 科学工程计算教育部重点实验室开放课题.

  4. 2019年6月-2019年12月, 项目负责人, ‘‘数据相关性分析及其数学建模方法", 泛亚汽车技术中心.

  5. 2018年1月-2020年12月, 项目负责人, ‘‘高维回归模型中的交互作用识别问题", 国家自然科学基金青年基金.

  6. 2016年6月-2019年5月, 项目负责人, ‘‘一类样本协方差矩阵的极限统计性质“, 上海市青年科技英才‘‘扬帆计划”项目.

  7. 2014年9月-2017年8月, 项目负责人, ‘‘大维数据判别分析研究", 上海交通大学特别研究员科研启动项目.

Publications

  1. Cheng Wang, Binyan Jiang and Liping Zhu, Penalized interaction estimation for ultrahigh dimensional quadratic regression, Statistica Sinica, in press, 2019+. (arxiv, R package PIE)

  2. Cheng Wang, Zhou Yu and Liping Zhu, On cumulative slicing estimation for high dimensional data, Statistica Sinica, in press, 2019+.

  3. Cheng Wang and Binyan Jiang, An efficient ADMM algorithm for high dimensional precision matrix estimation via penalized quadratic loss, Computational Statistics & Data Analysis, 142, 106812,2020. (arxiv, R package EQUAL )

  4. Zhou Tang, Zhangsheng Yu and Cheng Wang, A fast iterative algorithm for high-dimensional differential network, Computational Statistics, 35, 95-109, 2020. (arxiv, R package Diffnet)

  5. Cheng Wang and Binyan Jiang, On the dimension effect of regularized linear discriminant analysis, Electronic Journal of Statistics, 12, 2709-2742, 2018. (arxiv)

  6. Cheng Wang, Guangming Pan, Tiejun Tong and Lixing Zhu, Shrinkage estimation for large dimensional precision matrices using random matrix theory, Statistica Sinica, 25, 993-1008, 2015.

  7. Tiejun Tong, Cheng Wang, and Yuedong Wang, Estimation of variances and covariances for high-dimensional data: a selective review, WIREs Computational Statistics, 6, 255-264, 2014.

  8. Cheng Wang, Tiejun Tong, Longbing Cao and Baiqi Miao, Non-parametric shrinkage mean estimation for arbitrary quadratic loss functions and unknown covariance matrices, Journal of Multivariate Analysis, 125, 222-232, 2014. (arxiv)

  9. Cheng Wang, Asymptotic power of likelihood ratio tests for high dimensional data, Statistics & Probability Letters, 88, 184-189, 2014. (arxiv)

  10. Cheng Wang, Longbing Cao and Baiqi Miao, Optimal feature selection for sparse linear discriminant analysis and its applications in gene expression data, Computational Statistics & Data Analysis, 66, 140-149, 2013. (arxiv)

  11. Cheng Wang, Jing Yang, Baiqi Miao and Longbing Cao, Identity tests for high dimensional data using RMT, Journal of Multivariate Analysis, 118, 128-137, 2013. (arxiv)

  12. Cheng Wang, Baisuo Jin and Baiqi Miao, On limiting spectral distribution of large sample covariance matrices by VARMA (p, q), Journal of Time Series Analysis, 32(5), 539-546, 2011.

  13. Baisuo Jin, Cheng Wang, Baiqi Miao and Mong-Na Lo Huang, Limiting spectral distribution of large-dimensional sample covariance matrices generated by VARMA, Journal of Multivariate Analysis, 100, 2112-2125, 2009.

Cheng@Google Scholar Cheng@Github