T. Tony Cai | Academic Influence

T. Tony Cai's AcademicInfluence.com Rankings

T. Tony Cai

Mathematics

#2384

World Rank

#3704

Historical Rank

Statistics

#159

World Rank

#205

Historical Rank

mathematics Degrees

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Mathematics

T. Tony Cai's Degrees

PhD Statistics Stanford University
Masters Statistics Stanford University

Why Is T. Tony Cai Influential?

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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.

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T. Tony Cai'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

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)

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