4k citations · 6.4k across the 63 of their papers we have counts for
37 papers · 1 filter
Adaptive Linear Estimating Equations
Mufang Ying, Koulik Khamaru, Cun-Hui Zhang
Sequential data collection has emerged as a widely adopted technique for enhancing the efficiency of data gathering processes. Despite its advantages, such data collection mechanis…
Choosing the in loss: rate adaptivity on the symmetric location problem
Yu-Chun Kao, Min Xu, Cun-Hui Zhang
Given univariate random variables with the distribution, the sample midrange is the MLE for …
High-Order Statistical Functional Expansion and Its Application To Some Nonsmooth Problems
Fan Zhou, Ping Li, Cun-Hui Zhang
Let $\bx_j = \btheta +\bep_j, j=1,...,n$, be observations of an unknown parameter $\btheta$ in a Euclidean or separable Hilbert space $\scrH$, where $\bep_j$ are noises as random e…
Asymptotic normality of robust -estimators with convex penalty
Pierre C Bellec, Yiwei Shen, Cun-Hui Zhang
This paper develops asymptotic normality results for individual coordinates of robust M-estimators with convex penalty in high-dimensions, where the dimension is at most of the…
Adaptive Estimation In High-Dimensional Additive Models With Multi-Resolution Group Lasso
Yisha Yao, Cun-Hui Zhang
In additive models with many nonparametric components, a number of regularized estimators have been proposed and proven to attain various error bounds under different combinations…
Confidence intervals for multiple isotonic regression and other monotone models
Hang Deng, Qiyang Han, Cun-Hui Zhang
We consider the problem of constructing pointwise confidence intervals in the multiple isotonic regression model. Recently, [HZ19] obtained a pointwise limit distribution theory fo…
De-biasing convex regularized estimators and interval estimation in linear models
Pierre C Bellec, Cun-Hui Zhang
New upper bounds are developed for the distance between and linear and quadratic functions of for random variables of the form $ξ=bz^…
Decorrelated Local Linear Estimator: Inference for Non-linear Effects in High-dimensional Additive Models
Zijian Guo, Wei Yuan, Cun-Hui Zhang
Additive models play an essential role in studying non-linear relationships. Despite many recent advances in estimation, there is a lack of methods and theories for inference in hi…
Limit distribution theory for block estimators in multiple isotonic regression
Qiyang Han, Cun-Hui Zhang
We study limit distributions for the tuning-free max-min block estimator originally proposed in [FLN17] in the problem of multiple isotonic regression, under both fixed lattice des…
Extreme Eigenvalues of Nonlinear Correlation Matrices with Applications to Additive Models
Zijian Guo, Cun-Hui Zhang
The maximum correlation of functions of a pair of random variables is an important measure of stochastic dependence. It is known that this maximum nonlinear correlation is identica…
De-Biasing The Lasso With Degrees-of-Freedom Adjustment
Pierre C. Bellec, Cun-Hui Zhang
This paper studies schemes to de-bias the Lasso in a linear model where the goal is to construct confidence intervals for in a direction , where has iid…
Isotonic Regression in Multi-Dimensional Spaces and Graphs
Hang Deng, Cun-Hui Zhang
In this paper we study minimax and adaptation rates in general isotonic regression. For uniform deterministic and random designs in with and noise, the…
Second order Stein: SURE for SURE and other applications in high-dimensional inference
Pierre C Bellec, Cun-Hui Zhang
Stein's formula states that a random variable of the form is mean-zero for functions with integrable gradient. Here, is the diver…
Sorted Concave Penalized Regression
Long Feng, Cun-Hui Zhang
The Lasso is biased. Concave penalized least squares estimation (PLSE) takes advantage of signal strength to reduce this bias, leading to sharper error bounds in prediction, coeffi…
On Estimation of Isotonic Piecewise Constant Signals
Chao Gao, Fang Han, Cun-Hui Zhang
Consider a sequence of real data points with underlying means . This paper starts from studying the setting that is both piecewise cons…
Penalized Estimation in Additive Regression with High-Dimensional Data
Zhiqiang Tan, Cun-Hui Zhang
Additive regression provides an extension of linear regression by modeling the signal of a response as a sum of functions of covariates of relatively low complexity. We study penal…
Incoherent Tensor Norms and Their Applications in Higher Order Tensor Completion
Ming Yuan, Cun-Hui Zhang
In this paper, we investigate the sample size requirement for a general class of nuclear norm minimization methods for higher order tensor completion. We introduce a class of tenso…
Lasso adjustments of treatment effect estimates in randomized experiments
Adam Bloniarz, Hanzhong Liu, Cun-Hui Zhang +2
We provide a principled way for investigators to analyze randomized experiments when the number of covariates is large. Investigators often use linear multivariate regression to an…
The Benefit of Group Sparsity in Group Inference with De-biased Scaled Group Lasso
Ritwik Mitra, Cun-Hui Zhang
We study confidence regions and approximate chi-squared tests for variable groups in high-dimensional linear regression. When the size of the group is small, low-dimensional projec…
Multivariate Analysis of Nonparametric Estimates of Large Correlation Matrices
Ritwik Mitra, Cun-Hui Zhang
We study concentration in spectral norm of nonparametric estimates of correlation matrices. We work within the confine of a Gaussian copula model. Two nonparametric estimators of t…
Adaptive Threshold Estimation by FDR
Wenhua Jiang, Cun-Hui Zhang
This paper addresses the following simple question about sparsity. For the estimation of an -dimensional mean vector in the Gaussian sequence model, is it possibl…
Asymptotic normality and optimalities in estimation of large Gaussian graphical models
Zhao Ren, Tingni Sun, Cun-Hui Zhang +1
The Gaussian graphical model, a popular paradigm for studying relationship among variables in a wide range of applications, has attracted great attention in recent years. This pape…
Oracle inequalities for the lasso in the Cox model
Jian Huang, Tingni Sun, Zhiliang Ying +2
We study the absolute penalized maximum partial likelihood estimator in sparse, high-dimensional Cox proportional hazards regression models where the number of time-dependent covar…
Calibrated Elastic Regularization in Matrix Completion
Tingni Sun, Cun-Hui Zhang
This paper concerns the problem of matrix completion, which is to estimate a matrix from observations in a small subset of indices. We propose a calibrated spectrum elastic net met…