Underground space utilization of coalmines in China: A review of underground water reservoir construction
A large number of abandoned mines with sizeable underground space resources were
formed in China. Meanwhile, for an operational mine, the protection and utilization of mine …
formed in China. Meanwhile, for an operational mine, the protection and utilization of mine …
Coal pillar failure analysis and instability evaluation methods: A short review and prospect
Underground coal mining is characterized by the formation of extensive pillars. Coal pillars
serve various purposes, and their instability failure characteristics play a vital role in safety …
serve various purposes, and their instability failure characteristics play a vital role in safety …
[HTML][HTML] Strength weakening and its micromechanism in water–rock interaction, a short review in laboratory tests
Water–rock interaction (WRI) is a topic of interest in geology and geotechnical engineering.
Many geological hazards and engineering safety problems are severe under the WRI. This …
Many geological hazards and engineering safety problems are severe under the WRI. This …
Nearly unbiased variable selection under minimax concave penalty
CH Zhang - 2010 - projecteuclid.org
We propose MC+, a fast, continuous, nearly unbiased and accurate method of penalized
variable selection in high-dimensional linear regression. The LASSO is fast and continuous …
variable selection in high-dimensional linear regression. The LASSO is fast and continuous …
Confidence intervals for low dimensional parameters in high dimensional linear models
CH Zhang, SS Zhang - Journal of the Royal Statistical Society …, 2014 - academic.oup.com
The purpose of this paper is to propose methodologies for statistical inference of low
dimensional parameters with high dimensional data. We focus on constructing confidence …
dimensional parameters with high dimensional data. We focus on constructing confidence …
The sparsity and bias of the lasso selection in high-dimensional linear regression
Abstract Meinshausen and Buhlmann [Ann. Statist. 34 (2006) 1436–1462] showed that, for
neighborhood selection in Gaussian graphical models, under a neighborhood stability …
neighborhood selection in Gaussian graphical models, under a neighborhood stability …
Adaptive Lasso for sparse high-dimensional regression models
We study the asymptotic properties of the adaptive Lasso estimators in sparse, high-
dimensional, linear regression models when the number of covariates may increase with the …
dimensional, linear regression models when the number of covariates may increase with the …
Scaled sparse linear regression
T Sun, CH Zhang - Biometrika, 2012 - academic.oup.com
Scaled sparse linear regression jointly estimates the regression coefficients and noise level
in a linear model. It chooses an equilibrium with a sparse regression method by iteratively …
in a linear model. It chooses an equilibrium with a sparse regression method by iteratively …
The multivariate L1-median and associated data depth
Y Vardi, CH Zhang - … of the National Academy of Sciences, 2000 - National Acad Sciences
This paper gives three related results:(i) a new, simple, fast, monotonically converging
algorithm for deriving the L 1-median of a data cloud in ℝ d, a problem that can be traced to …
algorithm for deriving the L 1-median of a data cloud in ℝ d, a problem that can be traced to …
Optimal rates of convergence for covariance matrix estimation
Covariance matrix plays a central role in multivariate statistical analysis. Significant
advances have been made recently on developing both theory and methodology for …
advances have been made recently on developing both theory and methodology for …