Cun‐hui Zhang
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Cun‐hui Zhangmathematics Degrees
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Mathematics
Cun‐hui Zhang's Degrees
- PhD Statistics University of California, Berkeley
- Masters Statistics University of California, Berkeley
- Bachelors Mathematics Fudan University
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(Suggest an Edit or Addition)Cun‐hui Zhang's Published Works
Number of citations in a given year to any of this author's works
Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author
Published Works
- Nearly unbiased variable selection under minimax concave penalty (2010) (3045)
- Confidence intervals for low dimensional parameters in high dimensional linear models (2011) (887)
- The sparsity and bias of the Lasso selection in high-dimensional linear regression (2008) (830)
- Adaptive Lasso for sparse high-dimensional regression models (2008) (603)
- Scaled sparse linear regression (2011) (477)
- Optimal rates of convergence for covariance matrix estimation (2010) (433)
- A group bridge approach for variable selection (2009) (334)
- A General Theory of Concave Regularization for High-Dimensional Sparse Estimation Problems (2011) (314)
- Fourier Methods for Estimating Mixing Densities and Distributions (1990) (281)
- On Tensor Completion via Nuclear Norm Minimization (2014) (233)
- Asymptotic normality and optimalities in estimation of large Gaussian graphical models (2013) (223)
- Rate Minimaxity of the Lasso and Dantzig Selector for the lq Loss in lr Balls (2010) (211)
- General maximum likelihood empirical Bayes estimation of normal means (2009) (187)
- Correlated variables in regression: Clustering and sparse estimation (2012) (178)
- Sparse matrix inversion with scaled Lasso (2012) (156)
- Lasso adjustments of treatment effect estimates in randomized experiments (2015) (132)
- High-dimensional simultaneous inference with the bootstrap (2016) (121)
- One Permutation Hashing (2012) (115)
- ORACLE INEQUALITIES FOR THE LASSO IN THE COX MODEL. (2013) (110)
- Risk bounds in isotonic regression (2002) (105)
- Estimation in the Mean Residual Life Regression Model (1994) (99)
- Asymptotic equivalence theory for nonparametric regression with random design (2002) (96)
- The Sparse Laplacian Shrinkage Estimator for High-Dimensional Regression. (2011) (96)
- A modified Weiszfeld algorithm for the Fermat-Weber location problem (2001) (94)
- Mixed group ranks: preference and confidence in classifier combination (2004) (87)
- Large Sample Study of Empirical Distributions in a Random-Multiplicative Censoring Model (1992) (86)
- Compound decision theory and empirical bayes methods (2003) (85)
- Transelliptical Graphical Models (2012) (81)
- Statistical Foundations of Data Science (2020) (74)
- Equivalence theory for density estimation, Poisson processes and Gaussian white noise with drift (2004) (67)
- Confidence Intervals for Low-Dimensional Parameters With High-Dimensional Data (2011) (65)
- General empirical Bayes wavelet methods and exactly adaptive minimax estimation (2005) (61)
- PENALIZED LINEAR UNBIASED SELECTION (2007) (60)
- Estimating a Monotone Density from Censored Observations (1994) (57)
- Discussion: One-step sparse estimates in nonconcave penalized likelihood models (2008) (55)
- Estimation and Selection via Absolute Penalized Convex Minimization And Its Multistage Adaptive Applications (2011) (55)
- Incoherent Tensor Norms and Their Applications in Higher Order Tensor Completion (2016) (52)
- Asymptotic nonequivalence of nonparametric experiments when the smoothness index is (1998) (50)
- Factor Models for High-Dimensional Tensor Time Series (2019) (49)
- Optimality of graphlet screening in high dimensional variable selection (2012) (48)
- THE Mnet method for variable selection (2016) (48)
- Statistically Optimal and Computationally Efficient Low Rank Tensor Completion from Noisy Entries (2017) (47)
- Linear regression with doubly censored data (1996) (45)
- Estimation of sums of random variables: Examples and information bounds (2005) (43)
- Beyond Gaussian approximation: Bootstrap for maxima of sums of independent random vectors (2017) (42)
- The Benefit of Group Sparsity in Group Inference with De-biased Scaled Group Lasso (2014) (42)
- Group-Linear Empirical Bayes Estimates for a Heteroscedastic Normal Mean (2015) (40)
- Empirical Bayes in-season prediction of baseball batting averages (2010) (39)
- EMPIRICAL BAYES AND COMPOUND ESTIMATION OF NORMAL MEANS (1997) (39)
- Nonparametric methods for measurements below detection limit (2009) (38)
- Comments on: ℓ1-penalization for mixture regression models (2010) (37)
- A Two-Way Semilinear Model for Normalization and Analysis of cDNA Microarray Data (2005) (36)
- Asymptotic normality of a nonparametric estimator of sample coverage (2009) (34)
- What is the real size of a sampled network? The case of the Internet. (2007) (33)
- On Sample Size of the Kruskal–Wallis Test with Application to a Mouse Peritoneal Cavity Study (2011) (33)
- GENERALIZED MAXIMUM LIKELIHOOD ESTIMATION OF NORMAL MIXTURE DENSITIES (2009) (32)
- Linear regression with interval censored data (1998) (32)
- Confidence Intervals for Population Ranks in the Presence of Ties and Near Ties (2009) (31)
- Multivariate Analysis of Nonparametric Estimates of Large Correlation Matrices (2014) (30)
- On Estimating Mixing Densities in Discrete Exponential Family Models (1995) (29)
- Least squares estimators of the mode of a unimodal regression function (2001) (27)
- On estimation of isotonic piecewise constant signals (2017) (26)
- Rapid three-dimensional functional magnetic resonance imaging of the initial negative BOLD response. (2008) (25)
- Stepwise searching for feature variables in high-dimensional linear regression (2008) (24)
- Calibrated Elastic Regularization in Matrix Completion (2012) (23)
- Two-sample tests for growth curves under dependent right censoring (2001) (23)
- A Robust Clustering Method and Visualization Tool Based on Data Depth (2002) (23)
- A generalization of the two-dimensional prolate spheroidal wave function method for nonrectilinear MRI data acquisition methods (2006) (22)
- Rank Determination in Tensor Factor Model (2020) (20)
- Fast Functional Magnetic Resonance Imaging via Prolate Wavelets (2000) (20)
- De-biasing the lasso with degrees-of-freedom adjustment (2019) (20)
- Theory of the GMM Kernel (2016) (20)
- Complex datasets and inverse problems : tomography, networks and beyond (2007) (19)
- Two dimensional prolate spheroidal wave functions for MRI. (2002) (19)
- A Nonlinear Renewal Theory (1988) (19)
- A General Framework of Dual Certificate Analysis for Structured Sparse Recovery Problems (2012) (18)
- Second-order Stein: SURE for SURE and other applications in high-dimensional inference (2018) (18)
- Measures of Network Vulnerability (2007) (17)
- An iterative tomogravity algorithm for the estimation of network traffic (2007) (17)
- A New Algorithm for Compressed Counting with Applications in Shannon Entropy Estimation in Dynamic Data (2011) (17)
- Minimax Risk Bounds for Piecewise Constant Models (2017) (16)
- Poisson equation, moment inequalities and quick convergence for Markov random walks (2000) (16)
- Tensor Factor Model Estimation by Iterative Projection (2020) (16)
- An extension of the Hardy-Littlewood strong law (1997) (15)
- Isotonic regression in multi-dimensional spaces and graphs (2018) (15)
- Estimating a multiplicative treatment effect under biased allocation (1991) (15)
- ON OPTIMALITY OF BOLD PLAY FOR PRIMITIVE CASINOS IN THE PRESENCE OF INFLATION (2005) (15)
- One Permutation Hashing for Efficient Search and Learning (2012) (14)
- Doubly penalized estimation in additive regression with high-dimensional data (2019) (14)
- Compressed Counting Meets Compressed Sensing (2013) (14)
- Sorted concave penalized regression (2017) (13)
- Sub-bernoulli functions, moment inequalities and strong laws for nonnegative and symmetrized U-statistics (1999) (12)
- Re-randomized Densification for One Permutation Hashing and Bin-wise Consistent Weighted Sampling (2019) (12)
- A Comparison of Bias-Corrected Covariance Estimators for Generalized Estimating Equations (2013) (12)
- Generalized likelihood ratio test for normal mixtures (2016) (11)
- A Note on Feller's Strong Law of Large Numbers (1986) (11)
- A Two-Way Semi-Linear Model for Normalization and Significant Analysis of cDNA Microarray Data (2005) (11)
- STRONG LAW OF LARGE NUMBERS FOR SUMS OF PRODUCTS (1996) (11)
- Limit distribution theory for block estimators in multiple isotonic regression (2019) (10)
- On the Bitplane Compression of Microarray Images (2002) (10)
- THE ACQUISITION AND STATISTICAL ANALYSIS OF RAPID 3D FMRI DATA (2008) (10)
- On integrability in the LIL for degenerateU-statistics (1996) (10)
- Estimating Mixing Densities in Exponential Family Models for Discrete Variables (1997) (9)
- Compressed Sensing with Very Sparse Gaussian Random Projections (2014) (8)
- CP Factor Model for Dynamic Tensors (2021) (8)
- GLOBAL PROPERTIES OF KERNEL ESTIMATORS FOR MIXING DENSITIES IN DISCRETE EXPONENTIAL FAMILY MODELS (1996) (8)
- On the Almost Sure Minimal Growth Rate of Partial Sum Maxima (1994) (7)
- De-biasing convex regularized estimators and interval estimation in linear models (2019) (7)
- A RENEWAL THEORY WITH VARYING DRIFT (1989) (7)
- Continuous Generalized Gradient Descent (2007) (7)
- Network Inference from TraceRoute Measurements: Internet Topology 'Species' (2005) (7)
- Second order Poincaré inequalities and de-biasing arbitrary convex regularizers when $p/n \to γ$ (2019) (7)
- A Semi-linear Model for Normalization and Analysis of cDNA Microarray Data (2003) (7)
- Empirical Bayes methods for controlling the false discovery rate with dependent data (2007) (7)
- The Lower Limit of a Normalized Random Walk (1986) (7)
- High Dimensional Inference (2020) (6)
- Semi-Penalized Inference with Direct False Discovery Rate Control in High-Dimensions (2013) (6)
- Asymptotic properties of nonparametric maximum likelihood estimator for interval-truncated data (1995) (6)
- Confidence intervals for multiple isotonic regression and other monotone models (2020) (6)
- Reconstruction of Binary Images via the EM Algorithm (1999) (6)
- CONTINUOUS BLOOD GLUCOSE MONITORING: A BAYES-HIDDEN MARKOV APPROACH (2013) (5)
- Robust Small-Sample Inference for Fixed Effects in General Gaussian Linear Models (2012) (5)
- Exact sparse recovery with L0 projections (2013) (5)
- Sparse Recovery with Very Sparse Compressed Counting (2013) (5)
- L1-Depth, Depth Relative to a Model, and Robust Regression (2002) (5)
- The benefit of group sparsity in group inference with de-biased scaled group (2017) (5)
- Maximum likelihood estimation in regression with uniform errors (1986) (5)
- Penalized Estimation in Additive Regression with High-Dimensional Data (2017) (5)
- Information-Theoretic Optimality Of Variable Selection With Concave Penalty (2007) (5)
- Transelliptical Graphical Modeling under A Hierarchical Latent Variable Framework (2013) (5)
- Asymptotic Analysis of A Two-Way Semiparametric Regression Model for Microarray Data (2003) (4)
- Paths Following Algorithm for Penalized Logistic Regression Using SCAD and MCP (2014) (4)
- Entropy Estimations Using Correlated Symmetric Stable Random Projections (2012) (4)
- Asymptotically Efficient Allocation Rules for Two Bernoulli Populations (1992) (4)
- Rate Minimaxity of the Lasso and Dantzig Estimators (2009) (3)
- SIMULTANEOUS VARIABLE SELECTION AND OUTLIER DETECTION USING LASSO WITH APPLICATIONS TO AIRCRAFT LANDING DATA ANALYSIS (2012) (3)
- Central limit theorem for random convex chains (2000) (3)
- Asymptotic normality of robust M-estimators with convex penalty (2021) (3)
- Minimax ℓq risk in ℓp balls (2012) (3)
- Fast functional magnetic resonance imaging—a new approach towards neuroimaging (2008) (3)
- Tensor Principal Component Analysis in High Dimensional CP Models (2021) (3)
- Concave Learners for Rankboost (2007) (3)
- Poincaré inequalities and de-biasing arbitrary convex regularizers when p / n → γ (2019) (3)
- Pick Up Sticks (2012) (2)
- Nonlinear renewal theorems for random walks with perturbations of intermediate order (2006) (2)
- Adaptive Threshold Estimation by FDR (2013) (2)
- A decomposition for someU-type statistics (1996) (2)
- A nonparametric empirical Bayes approach to adaptive minimax estimation (2013) (2)
- Balancing stability and bias reduction in variable selection with the Mnet estimator (2013) (2)
- Extreme Nonlinear Correlation for Multiple Random Variables and Stochastic Processes with Applications to Additive Models (2019) (2)
- A Probability Model for Combining Ranks (2005) (2)
- Local Inference in Additive Models with Decorrelated Local Linear Estimator (2019) (2)
- A graphical approach to the analysis of matrix completion (2016) (2)
- SUPPLEMENT TO ”ASYMPTOTIC NORMALITY AND OPTIMALITIES IN ESTIMATION OF LARGE GAUSSIAN (2013) (2)
- Rate of divergence of the nonparametric likelihood ratio test for Gaussian mixtures (2019) (1)
- Limit distribution theory for multiple isotonic regression (2019) (1)
- Decorrelated Local Linear Estimator: Inference for Non-linear Effects in High-dimensional Additive Models (2019) (1)
- Rate-Optimal Subspace Estimation on Random Graphs (2021) (1)
- Mathematical aspects of estimating two treatment effects and a common variance in an assured allocation design (2002) (1)
- Some Moment and Exponential Inequalities for V-Statistics with Bounded Kernels (2001) (1)
- Simultaneous Decorrelation of Matrix Time Series* (2021) (1)
- High-Order Statistical Functional Expansion and Its Application To Some Nonsmooth Problems (2021) (1)
- Feature Screening (2020) (1)
- Discussion of minimax estimation of large covariance matrices under L1-Norm (2013) (1)
- Semi-Penalized Inference with False Discovery Rate Control in High-dimensional Linear Regression (2016) (0)
- Submitted to the Annals of Statistics ON ESTIMATION OF ISOTONIC PIECEWISE CONSTANT SIGNALS By (2018) (0)
- Statistical Inference for Structured High-dimensional Models (2019) (0)
- Rate adaptive estimation of the center of a symmetric distribution (2023) (0)
- Comment (2005) (0)
- Supervised Learning (2020) (0)
- Unsupervised Learning (2020) (0)
- ON THIE ALMOST SURE MJN(MAL GROWTH RATE OF PARTIAL (2016) (0)
- A Sequential Probability Ratio Test for Sparse Gaussian Mixtures (2022) (0)
- Covariance Regularization and Graphical Models (2020) (0)
- Introduction to Penalized Least-Squares (2020) (0)
- UNBIASED ESTIMATORS OF A LATTICE MIXING DISTRIBUTION AND THE CHARACTERISTIC FUNCTION OF A GENERAL MIXING DISTRIBUTION (1999) (0)
- THE LIMIT OF DISCRETE TGD AND CONTINUOUS NESTED TGD (2007) (0)
- On Tensor Completion via Nuclear Norm Minimization (2015) (0)
- ST ] 3 0 M ay 2 01 9 LIMIT DISTRIBUTION THEORY FOR MULTIPLE ISOTONIC REGRESSION QIYANG (2019) (0)
- Introduction (2020) (0)
- AN INVARIANT SELECTION RULE FOR MULTI-TREATMENT TRIAL WITH LINEAR PRIOR PREFERENCE (1997) (0)
- Generalized Linear Models and Penalized Likelihood (2020) (0)
- Imputation of automatic control algorithms and estimation in high-dimensional linear regression (2010) (0)
- THE UPPER LIMIT OF A NORMALIZED RANDOM WALK (2006) (0)
- Penalized Least Squares: Properties (2020) (0)
- Comment (2015) (0)
- Moments of Some Stopping Rules (1998) (0)
- Topics in Statistical Estimation and Control. (1996) (0)
- Rejoinder on: High-dimensional simultaneous inference with the bootstrap (2017) (0)
- Adaptive Estimation In High-Dimensional Additive Models With Multi-Resolution Group Lasso (2020) (0)
- Extreme eigenvalues of nonlinear correlation matrices with applications to additive models (2021) (0)
- Multiple and Nonparametric Regression (2020) (0)
- Applications of Factor Models and PCA (2020) (0)
- A Two-Way Semilinear Model for Normalization and Analysis of Microarray Data (2006) (0)
- Covariance Learning and Factor Models (2020) (0)
- Penalized M-estimators (2020) (0)
- Corrigendum (2014) (0)
- This paper gives three related results: (i) a new, simple, fast, monotonically converging algorithm for deriving the L1-median of a data cloud in (2000) (0)
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