Annals of Statistics

Article	Citations
Surprises in high-dimensional ridgeless least squares interpolation	96
Predictive inference with the jackknife+	90
E-values: Calibration, combination and applications	61
Learning models with uniform performance via distributionally robust optimization	50
A simple measure of conditional dependence	48
Time-uniform, nonparametric, nonasymptotic confidence sequences	46
Distribution and quantile functions, ranks and signs in dimension d: A measure transportation approach	46
On the rate of convergence of fully connected deep neural network regression estimates	45
Debiased inverse-variance weighted estimator in two-sample summary-data Mendelian randomization	43
Average treatment effects in the presence of unknown interference	36
Robust multivariate nonparametric tests via projection averaging	35
A shrinkage principle for heavy-tailed data: High-dimensional robust low-rank matrix recovery	34
Foundations of structural causal models with cycles and latent variables	33
Transfer learning for nonparametric classification: Minimax rate and adaptive classifier	32
Conformal prediction beyond exchangeability	31
Robust multivariate mean estimation: The optimality of trimmed mean	28
Linearized two-layers neural networks in high dimension	27
Approximate Message Passing algorithms for rotationally invariant matrices	27
On cross-validated Lasso in high dimensions	27
Estimation of low-rank matrices via approximate message passing	25
The cost of privacy: Optimal rates of convergence for parameter estimation with differential privacy	25
Extreme conditional expectile estimation in heavy-tailed heteroscedastic regression models	24
Optimal change point detection and localization in sparse dynamic networks	24
Distance-based and RKHS-based dependence metrics in high dimension	24
The distribution of the Lasso: Uniform control over sparse balls and adaptive parameter tuning	24

Adaptive transfer learning	23
Singular vector and singular subspace distribution for the matrix denoising model	23
Only closed testing procedures are admissible for controlling false discovery proportions	21
Empirical process results for exchangeable arrays	21
Simultaneous high-probability bounds on the false discovery proportion in structured, regression and online settings	21
Spiked separable covariance matrices and principal components	21
Classification accuracy as a proxy for two-sample testing	21
Bridging convex and nonconvex optimization in robust PCA: Noise, outliers and missing data	20
Minimax rates in sparse, high-dimensional change point detection	20
Construction of mixed orthogonal arrays with high strength	20
Asymptotically independent U-statistics in high-dimensional testing	20
Nonparametric drift estimation for i.i.d. paths of stochastic differential equations	20
Optimal rates of entropy estimation over Lipschitz balls	19
High-dimensional consistent independence testing with maxima of rank correlations	19
Improved central limit theorem and bootstrap approximations in high dimensions	19
Distributed linear regression by averaging	19
Optimality of spectral clustering in the Gaussian mixture model	19
An optimal statistical and computational framework for generalized tensor estimation	18
Fréchet change-point detection	18
Testing for outliers with conformal p-values	17
Minimax estimation of smooth optimal transport maps	17
Beyond Gaussian approximation: Bootstrap for maxima of sums of independent random vectors	17
Causal discovery in heavy-tailed models	17
Asymptotic distributions of high-dimensional distance correlation inference	16
Heteroskedastic PCA: Algorithm, optimality, and applications	16
Community detection on mixture multilayer networks via regularized tensor decomposition	16
Is infinity that far? A Bayesian nonparametric perspective of finite mixture models	16
Singularity, misspecification and the convergence rate of EM	16
Conditional calibration for false discovery rate control under dependence	15
Statistically optimal and computationally efficient low rank tensor completion from noisy entries	15
Inference for change points in high-dimensional data via selfnormalization	15
Distributed statistical inference for massive data	15
Augmented minimax linear estimation	14
Semiparametric optimal estimation with nonignorable nonresponse data	14
Peskun–Tierney ordering for Markovian Monte Carlo: Beyond the reversible scenario	14
Adaptive test of independence based on HSIC measures	14
Optimal adaptivity of signed-polygon statistics for network testing	14
Multivariate ranks and quantiles using optimal transport: Consistency, rates and nonparametric testing	14
Statistical guarantees for Bayesian uncertainty quantification in nonlinear inverse problems with Gaussian process priors	14
Factor-driven two-regime regression	14
Testing community structure for hypergraphs	14
Subspace estimation from unbalanced and incomplete data matrices: ℓ2,∞ statistical guarantees	14
Density deconvolution under general assumptions on the distribution of measurement errors	14
On universally consistent and fully distribution-free rank tests of vector independence	14
Convergence of covariance and spectral density estimates for high-dimensional locally stationary processes	13
Empirical Bayes oracle uncertainty quantification for regression	13
Deep learning for the partially linear Cox model	13
LASSO-driven inference in time and space	12
On extended admissible procedures and their nonstandard Bayes risk	12
Covariance estimation under one-bit quantization	12

Optimal rates for independence testing via U-statistic permutation tests	12
Statistical inference for principal components of spiked covariance matrices	12
Minimax optimal conditional independence testing	12
Powerful knockoffs via minimizing reconstructability	12
Marginal singularity and the benefits of labels in covariate-shift	12
Orthogonal statistical learning	11
Second-order Stein: SURE for SURE and other applications in high-dimensional inference	11
Measuring dependence in the Wasserstein distance for Bayesian nonparametric models	11
Robust sub-Gaussian estimation of a mean vector in nearly linear time	11
A precise high-dimensional asymptotic theory for boosting and minimum-ℓ1-norm interpolated classifiers	11
Random graph asymptotics for treatment effect estimation under network interference	11
Wasserstein $F$-tests and confidence bands for the Fréchet regression of density response curves	11
Estimation of the number of components of nonparametric multivariate finite mixture models	11
Additive regression for non-Euclidean responses and predictors	11
The interpolation phase transition in neural networks: Memorization and generalization under lazy training	11
Partial recovery for top-k ranking: Optimality of MLE and SubOptimality of the spectral method	10
Central limit theorem for linear spectral statistics of large dimensional Kendall’s rank correlation matrices and its applications	10
Admissible ways of merging p-values under arbitrary dependence	10
Consistent nonparametric estimation for heavy-tailed sparse graphs	10
Analysis of a two-layer neural network via displacement convexity	10
Isotonic regression in multi-dimensional spaces and graphs	10
Community detection with dependent connectivity	10
Fundamental barriers to high-dimensional regression with convex penalties	10
Monitoring for a change point in a sequence of distributions	10
Computational barriers to estimation from low-degree polynomials	10
Minimax optimality of permutation tests	10
Optimal difference-based variance estimators in time series: A general framework	9
Estimating the number of components in finite mixture models via the Group-Sort-Fuse procedure	9
Necessary and sufficient conditions for variable selection consistency of the LASSO in high dimensions	9
Precise statistical analysis of classification accuracies for adversarial training	9
Multivariate extensions of isotonic regression and total variation denoising via entire monotonicity and Hardy–Krause variation	9
The Lasso with general Gaussian designs with applications to hypothesis testing	9
Multiple block sizes and overlapping blocks for multivariate time series extremes	9
Central limit theorem and bootstrap approximation in high dimensions: Near 1/n rates via implicit smoothing	9
Max-sum tests for cross-sectional independence of high-dimensional panel data	9
Survival analysis via hierarchically dependent mixture hazards	8
Set structured global empirical risk minimizers are rate optimal in general dimensions	8
Integrative methods for post-selection inference under convex constraints	8
On fixed-domain asymptotics, parameter estimation and isotropic Gaussian random fields with Matérn covariance functions	8
An ℓp theory of PCA and spectral clustering	8
Asymptotic optimality in stochastic optimization	8
Asymptotics for spherical functional autoregressions	8
Approximate and exact designs for total effects	8
Optimal estimation of variance in nonparametric regression with random design	8
Strong selection consistency of Bayesian vector autoregressive models based on a pseudo-likelihood approach	8
Uniform convergence of local Fréchet regression with applications to locating extrema and time warping for metric space valued trajectories	8
Continuous-time targeted minimum loss-based estimation of intervention-specific mean outcomes	8
Estimation and inference in the presence of fractional d=1/2 and weakly nonstationary processes	7
Asymptotic properties of high-dimensional random forests	7
An asymptotic test for constancy of the variance under short-range dependence	7
Scalable estimation and inference for censored quantile regression process	7
Clustering in Block Markov Chains	7
Deep nonparametric regression on approximate manifolds: Nonasymptotic error bounds with polynomial prefactors	7
Edgeworth expansions for network moments	7
Irreducibility and geometric ergodicity of Hamiltonian Monte Carlo	7
Debiasing convex regularized estimators and interval estimation in linear models	7
Robust estimation of superhedging prices	7
Concentration of kernel matrices with application to kernel spectral clustering	7
Bounds on the conditional and average treatment effect with unobserved confounding factors	7
Wordlength enumerator for fractional factorial designs	7
Iterative algorithm for discrete structure recovery	7
Higher criticism to compare two large frequency tables, with sensitivity to possible rare and weak differences	7
Complex sampling designs: Uniform limit theorems and applications	7
False discovery rate control with unknown null distribution: Is it possible to mimic the oracle?	7
Dimension reduction for functional data based on weak conditional moments	7
Asymptotic joint distribution of extreme eigenvalues and trace of large sample covariance matrix in a generalized spiked population model	7
Prediction bounds for higher order total variation regularized least squares	6
Intrinsic Riemannian functional data analysis for sparse longitudinal observations	6
The distance standard deviation	6
Optimal full ranking from pairwise comparisons	6
Optimal estimation of high-dimensional Gaussian location mixtures	6
Existence and uniqueness of the Kronecker covariance MLE	6
Universal Bayes consistency in metric spaces	6
Frequentist validity of Bayesian limits	6
Bridging factor and sparse models	6
Detecting multiple replicating signals using adaptive filtering procedures	6
Cointegration in large VARs	6
Doubly debiased lasso: High-dimensional inference under hidden confounding	6
Nested Markov properties for acyclic directed mixed graphs	6
Reconciling the Gaussian and Whittle likelihood with an application to estimation in the frequency domain	6

Minimax estimation of smooth densities in Wasserstein distance	6
Towards optimal estimation of bivariate isotonic matrices with unknown permutations	6
Tensor clustering with planted structures: Statistical optimality and computational limits	6
Limit distribution theory for block estimators in multiple isotonic regression	6
Total variation regularized Fréchet regression for metric-space valued data	6
Propriety of the reference posterior distribution in Gaussian process modeling	6
Adaptive learning rates for support vector machines working on data with low intrinsic dimension	6
Testing goodness-of-fit and conditional independence with approximate co-sufficient sampling	6
Reconciling design-based and model-based causal inferences for split-plot experiments	6
Estimating minimum effect with outlier selection	6
Analysis of “learn-as-you-go” (LAGO) studies	6
Are deviations in a gradually varying mean relevant? A testing approach based on sup-norm estimators	6
Uncertainty quantification for Bayesian CART	5
Exact minimax risk for linear least squares, and the lower tail of sample covariance matrices	5
Asymmetry helps: Eigenvalue and eigenvector analyses of asymmetrically perturbed low-rank matrices	5
Coverage of credible intervals in nonparametric monotone regression	5
Asymptotic properties of penalized spline estimators in concave extended linear models: Rates of convergence	5
Rate-optimal robust estimation of high-dimensional vector autoregressive models	5
Inference for conditional value-at-risk of a predictive regression	5
Assessment of the extent of corroboration of an elaborate theory of a causal hypothesis using partial conjunctions of evidence factors	5
Concordance and value information criteria for optimal treatment decision	5
Nonlinear independent component analysis for discrete-time and continuous-time signals	5
High-dimensional latent panel quantile regression with an application to asset pricing	5
Global and individualized community detection in inhomogeneous multilayer networks	5
Total positivity in exponential families with application to binary variables	5
Grouped variable selection with discrete optimization: Computational and statistical perspectives	5
Efficiency of delayed-acceptance random walk Metropolis algorithms	5
Conditional predictive inference for stable algorithms	5
Matching recovery threshold for correlated random graphs	5
High-dimensional nonparametric density estimation via symmetry and shape constraints	5
Statistical inference in sparse high-dimensional additive models	5
Batch policy learning in average reward Markov decision processes	5
Rerandomization with diminishing covariate imbalance and diverging number of covariates	5
A causal bootstrap	5
Inference for low-rank models	5
A study of orthogonal array-based designs under a broad class of space-filling criteria	5
Asymptotic analysis of synchrosqueezing transform—toward statistical inference with nonlinear-type time-frequency analysis	5
Nonparametric Bayesian inference for reversible multidimensional diffusions	5
Confidence intervals for multiple isotonic regression and other monotone models	5
Multiscale Bayesian survival analysis	4
Adaptation in multivariate log-concave density estimation	4
On the optimality of sliced inverse regression in high dimensions	4
Correction note: Higher order elicitability and Osband’s principle	4
On robustness and local differential privacy	4
Local permutation tests for conditional independence	4
Settling the sample complexity of model-based offline reinforcement learning	4
Variable selection consistency of Gaussian process regression	4
Robust k-means clustering for distributions with two moments	4
ScreeNOT: Exact MSE-optimal singular value thresholding in correlated noise	4
Asymptotic distribution and convergence rates of stochastic algorithms for entropic optimal transportation between probability measures	4
Consistency of invariance-based randomization tests	4
Total positivity in multivariate extremes	4
Nonparametric regression on Lie groups with measurement errors	4
A convex optimization approach to high-dimensional sparse quadratic discriminant analysis	4
Rate-optimal cluster-randomized designs for spatial interference	4
What is resolution? A statistical minimax testing perspective on superresolution microscopy	4
Boosted nonparametric hazards with time-dependent covariates	4
Bootstrap long memory processes in the frequency domain	4
Relaxing the Gaussian assumption in shrinkage and SURE in high dimension	4
Toward theoretical understandings of robust Markov decision processes: Sample complexity and asymptotics	4
Optimal false discovery rate control for large scale multiple testing with auxiliary information	4
Optimal high-dimensional and nonparametric distributed testing under communication constraints	4
Post-selection inference via algorithmic stability	4
Nonregular and minimax estimation of individualized thresholds in high dimension with binary responses	4
Adaptive robust estimation in sparse vector model	4
The adaptive Wynn algorithm in generalized linear models with univariate response	4
Distributed nonparametric function estimation: Optimal rate of convergence and cost of adaptation	3
Two-level parallel flats designs	3
On the robustness of minimum norm interpolators and regularized empirical risk minimizers	3
Isotonic regression with unknown permutations: Statistics, computation and adaptation	3
Inference for a two-stage enrichment design	3
Analysis of generalized Bregman surrogate algorithms for nonsmooth nonconvex statistical learning	3
Optimal nonparametric testing of Missing Completely At Random and its connections to compatibility	3
Limit theorems for distributions invariant under groups of transformations	3
Infinite-dimensional gradient-based descent for alpha-divergence minimisation	3
Rank-based indices for testing independence between two high-dimensional vectors	3
Estimation of smooth functionals in normal models: Bias reduction and asymptotic efficiency	3
Uniform consistency in nonparametric mixture models	3
Bootstrapping persistent Betti numbers and other stabilizing statistics	3
Pattern graphs: A graphical approach to nonmonotone missing data	3
Spectral estimation of Hawkes processes from count data	3
A no-free-lunch theorem for multitask learning	3
Optimal change-point detection and localization	3
Volatility coupling	3
Adaptive estimation in multivariate response regression with hidden variables	3
Consistency of Bayesian inference for multivariate max-stable distributions	3
General and feasible tests with multiply-imputed datasets	3
Necessary and sufficient conditions for asymptotically optimal linear prediction of random fields on compact metric spaces	3
Single index Fréchet regression	3
Limiting distributions for eigenvalues of sample correlation matrices from heavy-tailed populations	3
Consistent order selection for ARFIMA processes	3
Local convexity of the TAP free energy and AMP convergence for Z2-synchronization	3
Optimal linear discriminators for the discrete choice model in growing dimensions	3
Sharp global convergence guarantees for iterative nonconvex optimization with random data	3
Principal components in linear mixed models with general bulk	3