# T. Tony Cai

#18,762

Most Influential Person Now

Statistician

## T. Tony Cai's AcademicInfluence.com Rankings

T. Tony Caimathematics Degrees

Mathematics

#2384

World Rank

#3704

Historical Rank

Statistics

#159

World Rank

#205

Historical Rank

## Download Badge

Mathematics

## T. Tony Cai's Degrees

- PhD Statistics Stanford University
- Masters Statistics Stanford University

## Why Is T. Tony Cai Influential?

(Suggest an Edit or Addition)According to Wikipedia, Tianwen Tony Cai is a Chinese statistician. He is the Daniel H. Silberberg Professor of Statistics and Vice Dean at the Wharton School of the University of Pennsylvania. He is also professor of Applied Math & Computational Science Graduate Group, and associate scholar at the Department of Biostatistics, Epidemiology & Informatics, Perelman School of Medicine, University of Pennsylvania. In 2008 Tony Cai was awarded the COPSS Presidents' Award.

## T. Tony Cai's Published Works

### Published Works

- Orthogonal Matching Pursuit for Sparse Signal Recovery With Noise (2011) (970)
- A Constrained ℓ1 Minimization Approach to Sparse Precision Matrix Estimation (2011) (967)
- Prediction in functional linear regression (2006) (512)
- Adaptive Thresholding for Sparse Covariance Matrix Estimation (2011) (512)
- Optimal rates of convergence for covariance matrix estimation (2010) (433)
- Incorporating Information on Neighboring Coefficients Into Wavelet Estimation (2001) (395)
- Adaptive wavelet estimation : A block thresholding and oracle inequality approach (1999) (364)
- Sparse PCA: Optimal rates and adaptive estimation (2012) (308)
- Confidence Intervals for a binomial proportion and asymptotic expansions (2002) (305)
- Oracle and Adaptive Compound Decision Rules for False Discovery Rate Control (2007) (293)
- Sparse Representation of a Polytope and Recovery of Sparse Signals and Low-Rank Matrices (2013) (286)
- A Direct Estimation Approach to Sparse Linear Discriminant Analysis (2011) (267)
- New Bounds for Restricted Isometry Constants (2009) (260)
- A Reproducing Kernel Hilbert Space Approach to Functional Linear Regression (2010) (234)
- Sharp RIP Bound for Sparse Signal and Low-Rank Matrix Recovery (2013) (231)
- OPTIMAL RATES OF CONVERGENCE FOR SPARSE COVARIANCE MATRIX ESTIMATION (2012) (225)
- Two-Sample Covariance Matrix Testing and Support Recovery in High-Dimensional and Sparse Settings (2013) (215)
- Shifting Inequality and Recovery of Sparse Signals (2010) (210)
- Optimal Rates of Convergence for Noisy Sparse Phase Retrieval via Thresholded Wirtinger Flow (2015) (208)
- Estimating the Null and the Proportion of Nonnull Effects in Large-Scale Multiple Comparisons (2006) (196)
- Estimating structured high-dimensional covariance and precision matrices: Optimal rates and adaptive estimation (2016) (195)
- Limiting laws of coherence of random matrices with applications to testing covariance structure and construction of compressed sensing matrices (2011) (178)
- Estimating Sparse Precision Matrix: Optimal Rates of Convergence and Adaptive Estimation (2012) (172)
- Stable Recovery of Sparse Signals and an Oracle Inequality (2010) (166)
- On Recovery of Sparse Signals via ℓ1 Minimization (2008) (162)
- Distributions of angles in random packing on spheres (2013) (156)
- Confidence intervals for high-dimensional linear regression: Minimax rates and adaptivity (2015) (155)
- On Recovery of Sparse Signals Via $\ell _{1}$ Minimization (2008) (152)
- Optimal estimation and rank detection for sparse spiked covariance matrices (2013) (150)
- One-sided confidence intervals in discrete distributions (2005) (141)
- WAVELET SHRINKAGE FOR NONEQUISPACED SAMPLES (1998) (140)
- Minimax and Adaptive Prediction for Functional Linear Regression (2012) (134)
- Robust and Computationally Feasible Community Detection in the Presence of Arbitrary Outlier Nodes (2014) (132)
- Rate-Optimal Perturbation Bounds for Singular Subspaces with Applications to High-Dimensional Statistics (2016) (129)
- Adaptive covariance matrix estimation through block thresholding (2012) (126)
- ROP: Matrix Recovery via Rank-One Projections (2013) (126)
- MINIMAX ESTIMATION OF LARGE COVARIANCE MATRICES UNDER ℓ1-NORM (2012) (122)
- Direct estimation of differential networks. (2014) (120)
- ON BLOCK THRESHOLDING IN WAVELET REGRESSION: ADAPTIVITY, BLOCK SIZE, AND THRESHOLD LEVEL (2002) (117)
- Effect of mean on variance function estimation in nonparametric regression (2008) (114)
- False discovery control in large‐scale spatial multiple testing (2015) (111)
- A data-driven block thresholding approach to wavelet estimation (2009) (109)
- Estimation and Confidence Sets for Sparse Normal Mixtures (2006) (105)
- Optimal hypothesis testing for high dimensional covariance matrices (2012) (104)
- Simultaneous Testing of Grouped Hypotheses: Finding Needles in Multiple Haystacks (2009) (103)
- Asymptotic equivalence theory for nonparametric regression with random design (2002) (96)
- Matrix completion via max-norm constrained optimization (2013) (96)
- An adaptation theory for nonparametric confidence intervals (2004) (94)
- Optimal estimation of the mean function based on discretely sampled functional data: Phase transition (2011) (91)
- Optimal adaptive estimation of a quadratic functional (1996) (89)
- The Cost of Privacy: Optimal Rates of Convergence for Parameter Estimation with Differential Privacy (2019) (85)
- Optimal rates of convergence for estimating Toeplitz covariance matrices (2013) (85)
- Testing composite hypotheses, Hermite polynomials and optimal estimation of a nonsmooth functional (2011) (83)
- Adaptive Confidence Balls (2006) (75)
- The root–unroot algorithm for density estimation as implemented via wavelet block thresholding (2010) (75)
- Optimal Sparse Segment Identification With Application in Copy Number Variation Analysis (2010) (73)
- Compressed Sensing and Affine Rank Minimization Under Restricted Isometry (2013) (72)
- Adaptive variance function estimation in heteroscedastic nonparametric regression (2008) (72)
- A difference based approach to the semiparametric partial linear model (2011) (68)
- Optimal rates of convergence for estimating the null density and proportion of nonnull effects in large-scale multiple testing (2010) (68)
- Phase transition in limiting distributions of coherence of high-dimensional random matrices (2011) (68)
- Limiting laws for divergent spiked eigenvalues and largest nonspiked eigenvalue of sample covariance matrices (2017) (64)
- Nonquadratic estimators of a quadratic functional (2005) (64)
- Structured Matrix Completion with Applications to Genomic Data Integration (2015) (61)
- Law of log determinant of sample covariance matrix and optimal estimation of differential entropy for high-dimensional Gaussian distributions (2013) (58)
- Enhanced Chemical Classification of Raman Images Using Multiresolution Wavelet Transformation (2001) (58)
- Joint Estimation of Multiple High-dimensional Precision Matrices. (2016) (57)
- On Adaptive Estimation of Linear Functionals (2005) (57)
- Optimal Detection of Sparse Mixtures Against a Given Null Distribution (2014) (56)
- Nonparametric regression in exponential families (2010) (56)
- Computational and Statistical Boundaries for Submatrix Localization in a Large Noisy Matrix (2015) (54)
- Covariate-Adjusted Precision Matrix Estimation with an Application in Genetical Genomics. (2013) (52)
- Minimax estimation of linear functionals over nonconvex parameter spaces (2004) (52)
- Robust nonparametric estimation via wavelet median regression (2008) (52)
- CHIME: Clustering of high-dimensional Gaussian mixtures with EM algorithm and its optimality (2019) (52)
- Heteroskedastic PCA: Algorithm, optimality, and applications (2018) (50)
- Large-Scale Multiple Testing of Correlations (2016) (50)
- Transfer learning for high‐dimensional linear regression: Prediction, estimation and minimax optimality (2020) (49)
- Simultaneous Discovery of Rare and Common Segment Variants. (2013) (47)
- Transfer Learning for Nonparametric Classification: Minimax Rate and Adaptive Classifier (2019) (47)
- Optimal False Discovery Rate Control for Dependent Data. (2011) (47)
- Variance function estimation in multivariate nonparametric regression with fixed design (2009) (46)
- Testing Differential Networks with Applications to Detecting Gene-by-Gene Interactions. (2015) (46)
- Weighted False Discovery Rate Control in Large-Scale Multiple Testing (2015) (45)
- High-dimensional sparse MANOVA (2014) (44)
- Orthogonal Matching Pursuit for Sparse Signal Recovery (2010) (39)
- Global Testing and Large-Scale Multiple Testing for High-Dimensional Covariance Structures (2017) (39)
- Accuracy assessment for high-dimensional linear regression (2016) (38)
- On adaptive wavelet estimation of a derivative and other related linear inverse problems (2002) (36)
- Nonparametric Covariance Function Estimation for Functional and Longitudinal Data (2010) (36)
- Adaptive confidence intervals for regression functions under shape constraints (2013) (36)
- Optimal Estimation of Genetic Relatedness in High-Dimensional Linear Models (2018) (36)
- Adaptive Confidence Bands for Nonparametric Regression Functions (2014) (33)
- A Framework For Estimation of Convex Functions (2015) (33)
- A note on nonparametric estimation of linear functionals (2003) (33)
- Minimax rate-optimal estimation of high-dimensional covariance matrices with incomplete data (2016) (31)
- RATES OF CONVERGENCE AND ADAPTATION OVER BESOV SPACES UNDER POINTWISE RISK (2003) (31)
- High-Dimensional Minimum Variance Portfolio Estimation Based on High-Frequency Data (2019) (29)
- Asymptotic Equivalence and Adaptive Estimation for Robust Nonparametric Regression (2009) (28)
- Discussion: "A significance test for the lasso" (2014) (27)
- More powerful genetic association testing via a new statistical framework for integrative genomics (2014) (27)
- Phenome‐Wide Association Study of Autoantibodies to Citrullinated and Noncitrullinated Epitopes in Rheumatoid Arthritis (2017) (26)
- Geometric Inference for General High-Dimensional Linear Inverse Problems (2014) (25)
- Inference for high-dimensional differential correlation matrices (2014) (25)
- Minimax and Adaptive Inference in Nonparametric Function Estimation (2012) (24)
- Optimal large-scale quantum state tomography with Pauli measurements (2016) (24)
- Semi-supervised inference: General theory and estimation of means (2016) (23)
- Distributed Gaussian Mean Estimation under Communication Constraints: Optimal Rates and Communication-Efficient Algorithms (2020) (23)
- Inference via Message Passing on Partially Labeled Stochastic Block Models (2016) (22)
- Nonparametric estimation over shrinking neighborhoods: Superefficiency and adaptation (2005) (21)
- Differential Markov random field analysis with an application to detecting differential microbial community networks. (2019) (20)
- Group inference in high dimensions with applications to hierarchical testing (2019) (19)
- Semi-supervised Inference for Explained Variance in High-dimensional Linear Regression and Its Applications (2018) (19)
- SHARP MINIMAX ESTIMATION OF THE VARIANCE OF BROWNIAN MOTION CORRUPTED WITH GAUSSIAN NOISE (2010) (19)
- High-Dimensional Gaussian Copula Regression: Adaptive Estimation and Statistical Inference (2015) (18)
- Sample size and power analysis for sparse signal recovery in genome-wide association studies. (2011) (18)
- Two-Sample Tests for High-Dimensional Linear Regression with an Application to Detecting Interactions. (2018) (17)
- Transfer Learning in Large-scale Gaussian Graphical Models with False Discovery Rate Control (2020) (17)
- The Cost of Privacy in Generalized Linear Models: Algorithms and Minimax Lower Bounds (2020) (16)
- Adaptive estimation of linear functionals under different performance measures (2005) (16)
- GAP: A General Framework for Information Pooling in Two-Sample Sparse Inference (2020) (16)
- Multiple Testing of Submatrices of a Precision Matrix With Applications to Identification of Between Pathway Interactions (2018) (16)
- Testing endogeneity with high dimensional covariates (2016) (15)
- On Detection and Structural Reconstruction of Small-World Random Networks (2016) (15)
- Statistical and Computational Limits for Sparse Matrix Detection (2018) (15)
- On information pooling, adaptability and superefficiency in nonparametric function estimation (2008) (15)
- Large-Scale Global and Simultaneous Inference: Estimation and Testing in Very High Dimensions (2017) (14)
- A convex optimization approach to high-dimensional sparse quadratic discriminant analysis (2019) (14)
- Trade-offs between global and local risks in nonparametric function estimation (2007) (13)
- Discussion: The Dantzig selector: Statistical estimation when p is much larger than n (2007) (13)
- Comment: Microarrays, Empirical Bayes and the Two-Group Model (2008) (12)
- Statistical Inference for High-Dimensional Generalized Linear Models with Binary Outcomes (2021) (12)
- Individualized Treatment Selection: An Optimal Hypothesis Testing Approach In High-dimensional Models (2019) (12)
- Rate-Optimal Detection of Very Short Signal Segments (2014) (11)
- LAWS: A Locally Adaptive Weighting and Screening Approach to Spatial Multiple Testing (2020) (11)
- Variance Function Estimation in Multivariate Nonparametric Regression (2006) (11)
- On Adaptivity Of BlockShrink Wavelet Estimator Over Besov Spaces (1997) (11)
- Sparse Group Lasso: Optimal Sample Complexity, Convergence Rate, and Statistical Inference (2019) (11)
- Joint testing and false discovery rate control in high‐dimensional multivariate regression (2018) (10)
- Theoretical Foundations of t-SNE for Visualizing High-Dimensional Clustered Data (2021) (10)
- On the non-asymptotic concentration of heteroskedastic Wishart-type matrix (2020) (10)
- Minimax and Adaptive Estimation of Covariance Operator for Random Variables Observed on a Lattice Graph (2016) (9)
- Sparse Simultaneous Signal Detection for Identifying Genetically Controlled Disease Genes (2017) (9)
- Estimation, Confidence Intervals, and Large-Scale Hypotheses Testing for High-Dimensional Mixed Linear Regression (2020) (9)
- Optimal Estimation of Co-heritability in High-dimensional Linear Models (2016) (8)
- Weighted Message Passing and Minimum Energy Flow for Heterogeneous Stochastic Block Models with Side Information (2017) (8)
- Optimal Detection For Sparse Mixtures (2012) (8)
- Inference for High-Dimensional Linear Mixed-Effects Models: A Quasi-Likelihood Approach (2019) (8)
- Optimal Structured Principal Subspace Estimation: Metric Entropy and Minimax Rates (2020) (8)
- Optimal estimation of bacterial growth rates based on a permuted monotone matrix (2020) (6)
- Inference on High-dimensional Differential Correlation Matrix (2014) (6)
- On Adaptability And Information Pooling in Nonparametric Function Estimation (2000) (6)
- On Modulus of Continuity And Adaptability in Nonparametric Functional Estimation (2002) (6)
- Geometrizing Local Rates of Convergence for High-Dimensional Linear Inverse Problems (2014) (6)
- Adaptive estimation of planar convex sets (2015) (6)
- Optimal estimation and rank detection for sparse spiked covariance matrices (2014) (6)
- Large-Scale Simultaneous Testing of Cross-Covariance Matrices with Applications to PheWAS. (2019) (5)
- Hypothesis testing for phylogenetic composition: a minimum-cost flow perspective. (2020) (5)
- SIHR: Statistical Inference in High-Dimensional Linear and Logistic Regression Models (2021) (5)
- Wavelet Regression via Block Thresholding: Adaptivity and the Choice of Block Size and Threshold Lev (1999) (5)
- Sparse Topic Modeling: Computational Efficiency, Near-Optimal Algorithms, and Statistical Inference (2021) (5)
- Optimal detection of weak positive latent dependence between two sequences of multiple tests (2014) (4)
- Distributed Nonparametric Function Estimation: Optimal Rate of Convergence and Cost of Adaptation (2021) (4)
- Asymptotic Analysis for Extreme Eigenvalues of Principal Minors of Random Matrices (2019) (4)
- Adaptive functional linear regression via functional principal component analysis and block thresholding (2018) (4)
- Optimal Adaptive Estimation of a Quadratic Functional 1 (2006) (4)
- Statistical Inference for Genetic Relatedness Based on High-Dimensional Logistic Regression (2022) (4)
- Supplement to “ Adaptive Thresholding for Sparse Covariance Matrix Estimation ” (2011) (3)
- Discussion of “Influential feature PCA for high dimensional clustering” (2016) (3)
- Distributed adaptive Gaussian mean estimation with unknown variance: Interactive protocol helps adaptation (2022) (3)
- Optimal Estimation of Wasserstein Distance on a Tree With an Application to Microbiome Studies (2020) (3)
- Wavelet Regression For Random Uniform Design (1997) (3)
- High Dimensional M-Estimation with Missing Outcomes: A Semi-Parametric Framework (2019) (3)
- Discussion of “ Regularization of Wavelets Approximations ” by A . Antoniadis and (2003) (3)
- Locally Adaptive Transfer Learning Algorithms for Large-Scale Multiple Testing (2022) (3)
- Optimal and Adaptive Estimation of Extreme Values in the Permuted Monotone Matrix Model (2019) (3)
- Global testing against sparse alternatives in time-frequency analysis (2014) (3)
- Recent results on sparse principle component analysis (2013) (2)
- Optimal Sparse Eigenspace and Low-Rank Density Matrix Estimation for Quantum Systems. (2021) (2)
- Matrix Reordering for Noisy Disordered Matrices: Optimality and Computationally Efficient Algorithms (2022) (2)
- SUPPLEMENT TO “LIMITING LAWS OF COHERENCE OF RANDOM MATRICES WITH APPLICATIONS TO TESTING COVARIANCE STRUCTURE AND CONSTRUCTION OF COMPRESSED SENSING (2011) (2)
- Correction to the paper “Optimal False Discovery Rate Control for Dependent Data” (2016) (2)
- Stochastic continuum-armed bandits with additive models: Minimax regrets and adaptive algorithm (2022) (2)
- Gaussianization Machines for Non-Gaussian Function Estimation Models (2019) (1)
- Optimal Estimation of A Quadratic Functional and Detection of Simultaneous Signals (2015) (1)
- Microarrays, Empirical Bayes and the Two-Groups Model. Comment. (2008) (1)
- Introduction to the Lehmann special section (2012) (1)
- Score Attack: A Lower Bound Technique for Optimal Differentially Private Learning (2023) (1)
- Supplement to “ A Framework For Estimation of Convex Functions ” (2012) (1)
- A Compound Decision-Theoretic Approach to Large-Scale Multiple Testing (2010) (1)
- OPTIMAL ESTIMATION OF A QUADRATIC FUNCTIONAL UNDER THE GAUSSIAN TWO-SEQUENCE MODEL (2016) (0)
- False Discovery Rate Control for High Dimensional Dependent Data with an Application to Large-Scale Genetic Association Studies (2010) (0)
- Comment (2010) (0)
- Statistical Inference in High-dimensional Regression (2021) (0)
- Signal Classification for the Integrative Analysis of Multiple Sequences of Multiple Tests (2017) (0)
- Transfer Learning for Contextual Multi-armed Bandits (2022) (0)
- Testing High-dimensional Multinomials with Applications to Text Analysis (2023) (0)
- Multiscale Methods and Statistics: A Productive Marriage (2009) (0)
- Neighborhood-Empowered Adaptive Transfer Learning for Large-Scale Multiple Testing (2022) (0)
- Department of Statistics -statistics Seminar – Spring 2011 Title: on Optimal Estimation of a Nonsmooth Functional Title: Entire Relaxation Path for Maximum Entropy Models (2015) (0)
- Estimation and Inference for Minimizer and Minimum of Convex Functions: Optimality, Adaptivity, and Uncertainty Principles (2023) (0)
- Average Case Analysis of Sparse Multivariate Regression under Noise (2010) (0)
- Goal A Gaussianization Machine + Non-Gaussian Function Estimation Model � ! Binning + Transformation � ! Standard Gaussian Regression Model (2019) (0)
- ADAPTIVE COVARIANCE MATRIX ESTIMATION THROUGH (2014) (0)
- Frontiers in Nonparametric Statistics (2012) (0)
- A Sparse PCA Approach to Clustering (2016) (0)
- Optimal Estimation of Simultaneous Signals Using Absolute Inner Product with Applications to Integrative Genomics (2018) (0)
- Archiving and retrieval of sequential images from tomographic databases in PACS (1998) (0)
- Optimal detection of weak positive dependence between two mixture distributions (2014) (0)
- Editorial (2009) (0)
- MINIMAX ESTIMATION OF LARGE COVARIANCE MATRICES 1321 matrices in Bickel and Levina (2012) (0)
- SPARSE SEGMENT IDENTIFICATIONS WITH APPLICATIONS TO DNA COPY NUMBER VARIATION ANALYSIS (2015) (0)
- Estimation and Inference for High-Dimensional Generalized Linear Models with Knowledge Transfer (2023) (0)
- Adaptive Functional Linear Regression (2008) (0)
- Statistical Inference and Large-scale Multiple Testing for High-dimensional Regression Models (2023) (0)
- ON ADAPTIVE ESTIMATION OF LINEAR FUNCTIONALS1 BY T. TONY CAI (2005) (0)
- Estimation and Inference with Proxy Data and its Genetic Applications (2022) (0)
- Optimal rates of convergence for estimating Toeplitz covariance matrices (2012) (0)
- NONQUADRATIC ESTIMATORS OF A QUADRATIC FUNCTIONAL1 BY T. TONY CAI (2006) (0)

This paper list is powered by the following services:

## Other Resources About T. Tony Cai

## What Schools Are Affiliated With T. Tony Cai?

T. Tony Cai is affiliated with the following schools: