Articles with public access mandates - Cun-Hui ZhangLearn more
Not available anywhere: 1
Supplement to “Beyond Gaussian approximation: Bootstrap for maxima of sums of independent random vectors.”
H Deng, CH Zhang
Mandates: US National Science Foundation
Available somewhere: 38
The sparsity and bias of the lasso selection in high-dimensional linear regression
CH Zhang, J Huang
Mandates: US National Institutes of Health
A group bridge approach for variable selection
J Huang, S Ma, H Xie, CH Zhang
Biometrika 96 (2), 339-355, 2009
Mandates: US National Institutes of Health
On tensor completion via nuclear norm minimization
M Yuan, CH Zhang
Foundations of Computational Mathematics 16 (4), 1031-1068, 2016
Mandates: US National Science Foundation, US National Institutes of Health
Lasso adjustments of treatment effect estimates in randomized experiments
A Bloniarz, H Liu, CH Zhang, JS Sekhon, B Yu
Proceedings of the National Academy of Sciences 113 (27), 7383-7390, 2016
Mandates: US National Science Foundation
High-dimensional simultaneous inference with the bootstrap
R Dezeure, P Bühlmann, CH Zhang
Test 26, 685-719, 2017
Mandates: US National Science Foundation, Swiss National Science Foundation, US …
Oracle inequalities for the lasso in the Cox model
J Huang, T Sun, Z Ying, Y Yu, CH Zhang
Annals of statistics 41 (3), 1142, 2013
Mandates: US National Institutes of Health
Factor models for high-dimensional tensor time series
R Chen, D Yang, CH Zhang
Journal of the American Statistical Association 117 (537), 94-116, 2022
Mandates: US National Science Foundation, Research Grants Council, Hong Kong
The sparse Laplacian shrinkage estimator for high-dimensional regression
J Huang, S Ma, H Li, CH Zhang
Annals of statistics 39 (4), 2021, 2011
Mandates: US National Institutes of Health
The Mnet method for variable selection
J Huang, P Breheny, S Lee, S Ma, CH Zhang
Statistica Sinica, 903-923, 2016
Mandates: US National Science Foundation, US National Institutes of Health
Statistically optimal and computationally efficient low rank tensor completion from noisy entries
D Xia, M Yuan, CH Zhang
Mandates: US National Science Foundation
Estimation and selection via absolute penalized convex minimization and its multistage adaptive applications
J Huang, CH Zhang
The Journal of Machine Learning Research 13 (1), 1839-1864, 2012
Mandates: US National Institutes of Health
Incoherent tensor norms and their applications in higher order tensor completion
M Yuan, CH Zhang
IEEE Transactions on Information Theory 63 (10), 6753-6766, 2017
Mandates: US National Science Foundation, US National Institutes of Health
The benefit of group sparsity in group inference with de-biased scaled group lasso
R Mitra, CH Zhang
Mandates: US National Science Foundation
Optimality of graphlet screening in high dimensional variable selection
J Jin, CH Zhang, Q Zhang
The Journal of Machine Learning Research 15 (1), 2723-2772, 2014
Mandates: US National Institutes of Health
Rank determination in tensor factor model
Y Han, R Chen, CH Zhang
Electronic Journal of Statistics 16 (1), 1726-1803, 2022
Mandates: US National Science Foundation
BEYOND GAUSSIAN APPROXIMATION
H Deng, CH Zhang
The Annals of Statistics 48 (6), 3643-3671, 2020
Mandates: US National Science Foundation
Group-linear empirical Bayes estimates for a heteroscedastic normal mean
A Weinstein, Z Ma, LD Brown, CH Zhang
Journal of the American Statistical Association 113 (522), 698-710, 2018
Mandates: US National Science Foundation
SECOND-ORDER STEIN
PC Bellec, CH Zhang
The Annals of Statistics 49 (4), 1864-1903, 2021
Mandates: US National Science Foundation
Doubly penalized estimation in additive regression with high-dimensional data
Z Tan, CH Zhang
Mandates: US National Science Foundation, Patient-Centered Outcomes Research Institute
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