Annals of Statistics

Article	Citations
Estimation and inference for minimizer and minimum of convex functions: Optimality, adaptivity and uncertainty principles	149
Debiased regression adjustment in completely randomized experiments with moderately high-dimensional covariates	55
High-dimensional statistical inference for linkage disequilibrium score regression and its cross-ancestry extensions	54
On high-dimensional Poisson models with measurement error: Hypothesis testing for nonlinear nonconvex optimization	44
Half-trek criterion for identifiability of latent variable models	41
Inference in Ising models on dense regular graphs	38
Deep horseshoe Gaussian processes	35
Efficiency in local differential privacy	33
Near-optimal inference in adaptive linear regression	33
Universal rank inference via residual subsampling with application to large networks	29
Optimal convex M-estimation via score matching	28
Scalable estimation and inference for censored quantile regression process	28
A sieve stochastic gradient descent estimator for online nonparametric regression in Sobolev ellipsoids	27
Deep learning for the partially linear Cox model	25
A geometrical analysis of kernel ridge regression and its applications	25
Fundamental limits of community detection from multi-view data: Multi-layer, dynamic and partially labeled block models	24
Learning sparse graphons and the generalized Kesten–Stigum threshold	23
Trace test for high-dimensional cointegration	22
Inference for low-rank models	22
Rank tests for PCA under weak identifiability	22
A general characterization of optimal tie-breaker designs	22
Asymptotic analysis of synchrosqueezing transform—toward statistical inference with nonlinear-type time-frequency analysis	21
Spectral gap bounds for reversible hybrid Gibbs chains	20
Consistent inference for diffusions from low frequency measurements	19
Adaptive and robust multi-task learning	19

Uniform convergence of local Fréchet regression with applications to locating extrema and time warping for metric space valued trajectories	19
Spectrum-aware debiasing: A modern inference framework with applications to principal components regression	18
Nonparametric classification with missing data	18
Yurinskii’s coupling for martingales	18
Testing goodness-of-fit and conditional independence with approximate co-sufficient sampling	18
Sharp optimality for high-dimensional covariance testing under sparse signals	18
On posterior consistency of data assimilation with Gaussian process priors: The 2D-Navier–Stokes equations	18
Near optimal sample complexity for matrix and tensor normal models via geodesic convexity	17
Environment invariant linear least squares	17
Fixed and random covariance regression analyses	16
Consistent order selection for ARFIMA processes	16
Is infinity that far? A Bayesian nonparametric perspective of finite mixture models	16
Rate-optimal estimation of mixed semimartingales	16
A common-cause principle for eliminating selection bias in causal estimands through covariate adjustment	16
Supervised homogeneity fusion: A combinatorial approach	16
Rank and factor loadings estimation in time series tensor factor model by pre-averaging	15
Spectral estimation of Hawkes processes from count data	15
Change-point inference in high-dimensional regression models under temporal dependence	15
On the structural dimension of sliced inverse regression	15
Limiting distributions for eigenvalues of sample correlation matrices from heavy-tailed populations	15
Order-of-addition orthogonal arrays to study the effect of treatment ordering	15
On the multiway principal component analysis	15
On the convergence of coordinate ascent variational inference	14
Consistency of Bayesian inference for multivariate max-stable distributions	14
General spatio-temporal factor models for high-dimensional random fields on a lattice	14
Toward theoretical understandings of robust Markov decision processes: Sample complexity and asymptotics	14
New Edgeworth-type expansions with finite sample guarantees	14
Object detection under the linear subspace model with application to cryo-EM images	14
The numeraire e-variable and reverse information projection	14
A nonparametric test for elliptical distribution based on kernel embedding of probabilities	14
Algorithmic stability implies training-conditional coverage for distribution-free prediction methods	13
Asymptotic distribution of maximum likelihood estimator in generalized linear mixed models with crossed random effects	13
Transfer learning for contextual multi-armed bandits	13
Wald tests when restrictions are locally singular	13
Plugin estimation of smooth optimal transport maps	13
Computational lower bounds for graphon estimation via low-degree polynomials	13
Consistency of invariance-based randomization tests	13
Sup-norm adaptive drift estimation for multivariate nonreversible diffusions	13
Minimax rate of distribution estimation on unknown submanifolds under adversarial losses	13
Minimax rate for multivariate data under componentwise local differential privacy constraints	13
Communication-efficient and distributed-oracle estimation for high-dimensional quantile regression	13
Testing nonparametric shape restrictions	12
The Lasso with general Gaussian designs with applications to hypothesis testing	12
Change acceleration and detection	12
Sharp adaptive and pathwise stable similarity testing for scalar ergodic diffusions	12
Time-uniform central limit theory and asymptotic confidence sequences	12
Linear biomarker combination for constrained classification	12
Projected state-action balancing weights for offline reinforcement learning	12
Learning mixtures of permutations: Groups of pairwise comparisons and combinatorial method of moments	12
A new approach to tests and confidence bands for distribution functions	11

Finite-sample complexity of sequential Monte Carlo estimators	11
Testing for independence in high dimensions based on empirical copulas	11
Noisy linear inverse problems under convex constraints: Exact risk asymptotics in high dimensions	11
Interactive versus noninteractive locally differentially private estimation: Two elbows for the quadratic functional	11
Detecting multiple replicating signals using adaptive filtering procedures	10
The Stein effect for Fréchet means	10
Nonlinear global Fréchet regression for random objects via weak conditional expectation	10
Dispersal density estimation across scales	10
Dimension free ridge regression	10
A flexible defense against the winner’s curse	10
Bridging factor and sparse models	10
Confidence regions near singular information and boundary points with applications to mixed models	10
Confounder selection via iterative graph expansion	10
The distributionally robust prediction error of the LASSO and related estimators	10
Carving model-free inference	10
ARK: Robust knockoffs inference with coupling	9
Ridge regression revisited: Debiasing, thresholding and bootstrap	9
On universally consistent and fully distribution-free rank tests of vector independence	9
ℓ2 inference for change points in high-dimensional time series via a Two-Way MOSUM	9
On the sample complexity of entropic optimal transport	9
Correction note: “Asymptotic spectral theory for nonlinear time series”	8
Online estimation with rolling validation: Adaptive nonparametric estimation with streaming data	8
Semiparametric inference based on adaptively collected data	8
Large-dimensional independent component analysis: Statistical optimality and computational tractability	8
Asymptotic distributions of largest Pearson correlation coefficients under dependent structures	8
Testing high-dimensional regression coefficients in linear models	8
Information theoretic limits of robust sub-Gaussian mean estimation under star-shaped constraints	8
Local convexity of the TAP free energy and AMP convergence for Z2-synchronization	7
Joint sequential detection and isolation for dependent data streams	7
Dualizing Le Cam’s method for functional estimation I: General theory	7
Symmetry: A general structure in nonparametric regression	7
Post-selection inference via algorithmic stability	7
A nonparametric doubly robust test for a continuous treatment effect	7
Matching recovery threshold for correlated random graphs	7
Entrywise dynamics and universality of general first order methods	7
Bootstrapping persistent Betti numbers and other stabilizing statistics	7
Rerandomization with diminishing covariate imbalance and diverging number of covariates	7
The online closure principle	7
Heavy-tailed Bayesian nonparametric adaptation	7
Affine-equivariant inference for multivariate location under Lp loss functions	7
Conformal inference for random objects	7
Ensemble projection pursuit for general nonparametric regression	7
Multivariate trend filtering for lattice data	7
Embedding distributional data	7
Spectral analysis of gram matrices with missing at random observations: Convergence, central limit theorems, and applications in statistical inference	7
Efficient estimation of the maximal association between multiple predictors and a survival outcome	7
Stereographic Markov chain Monte Carlo	6
Adaptive variational Bayes: Optimality, computation and applications	6
Global and individualized community detection in inhomogeneous multilayer networks	6
Some theory about efficient dimension reduction regarding the interaction between two responses	6
Estimating a density near an unknown manifold: A Bayesian nonparametric approach	6
Approximation error from discretizations and its applications	6
Optimal signal detection in some spiked random matrix models: Likelihood ratio tests and linear spectral statistics	6
A two-way heterogeneity model for dynamic networks	6
Local permutation tests for conditional independence	6
Kurtosis-based projection pursuit for matrix-valued data	6
Rates of estimation for high-dimensional multireference alignment	6
Universal regression with adversarial responses	6
A general framework to quantify deviations from structural assumptions in the analysis of nonstationary function-valued processes	6
On robustness and local differential privacy	6
Self-normalized Cramér type moderate deviation theorem for Gaussian approximation	6
Total positivity in multivariate extremes	6
Adaptive novelty detection with false discovery rate guarantee	6
Improved covariance estimation: Optimal robustness and sub-Gaussian guarantees under heavy tails	5
Asymptotically-exact selective inference for quantile regression	5
A study of orthogonal array-based designs under a broad class of space-filling criteria	5
Gaussian process regression in the flat limit	5
Statistical complexity and optimal algorithms for nonlinear ridge bandits	5
Rate-optimal robust estimation of high-dimensional vector autoregressive models	5
Semiparametric Bernstein–von Mises phenomenon via Isotonized Posterior in Wicksell’s problem	5
Convex regression in multidimensions: Suboptimality of least squares estimators	5
Conditional calibration for false discovery rate control under dependence	5
A new and flexible design construction for orthogonal arrays for modern applications	5
Central limit theorem and bootstrap approximation in high dimensions: Near 1/n rates via implicit smoothing	5
Model selection in the space of Gaussian models invariant by symmetry	5
Conditional predictive inference for stable algorithms	5
Grouped variable selection with discrete optimization: Computational and statistical perspectives	5
S-estimation in linear models with structured covariance matrices	5
Optimal subgroup selection	5
On the existence of powerful p-values and e-values for composite hypotheses	5

Deep neural networks for nonparametric interaction models with diverging dimension	5
Bootstrap-assisted inference for generalized Grenander-type estimators	5
Estimation of the spectral measure from convex combinations of regularly varying random vectors	5
A unified analysis of likelihood-based estimators in the Plackett–Luce model	5
Skewed Bernstein–von Mises theorem and skew-modal approximations	5
Scalable inference in functional linear regression with streaming data	5
Structured matrix learning under arbitrary entrywise dependence and estimation of Markov transition kernel	5
Convergence of de Finetti’s mixing measure in latent structure models for observed exchangeable sequences	4
MARS via LASSO	4
Concentration of discrepancy-based approximate Bayesian computation via Rademacher complexity	4
Uniform consistency in nonparametric mixture models	4
Quantile processes and their applications in finite populations	4
Spectral statistics of sample block correlation matrices	4
Higher criticism to compare two large frequency tables, with sensitivity to possible rare and weak differences	4
Tests of missing completely at random based on sample covariance matrices	4
Precise asymptotics of bagging regularized M-estimators	4
Finite- and large sample inference for model and coefficients in high-dimensional linear regression with repro samples	4
A conformal test of linear models via permutation-augmented regressions	4
The curse of overparametrization in adversarial training: Precise analysis of robust generalization for random features regression	4
Distributed adaptive Gaussian mean estimation with unknown variance: Interactive protocol helps adaptation	4
The generalization error of max-margin linear classifiers: Benign overfitting and high dimensional asymptotics in the overparametrized regime	4
Deep approximate policy iteration	4
Stochastic continuum-armed bandits with additive models: Minimax regrets and adaptive algorithm	4
Non-independent component analysis	4
Theory of functional principal component analysis for discretely observed data	4
The edge of discovery: Controlling the local false discovery rate at the margin	4
Learning low-dimensional nonlinear structures from high-dimensional noisy data: An integral operator approach	4
Optimal difference-based variance estimators in time series: A general framework	4
Generalized multilinear models for sufficient dimension reduction on tensor-valued predictors	4
Extreme value inference for heterogeneous power law data	4
One-step estimation of differentiable Hilbert-valued parameters	4
How do noise tails impact on deep ReLU networks?	4
Semi-supervised U-statistics	4
Fundamental limits of low-rank matrix estimation with diverging aspect ratios	4
Exact minimax risk for linear least squares, and the lower tail of sample covariance matrices	4
StarTrek: Combinatorial variable selection with false discovery rate control	4
Asymptotic normality and optimality in nonsmooth stochastic approximation	4
High-dimensional inference for dynamic treatment effects	4
Optimal policy evaluation using kernel-based temporal difference methods	4
Precise error rates for computationally efficient testing	4
Random graph asymptotics for treatment effect estimation under network interference	4
Early stopping for L2-boosting in high-dimensional linear models	4
A statistical framework of watermarks for large language models: Pivot, detection efficiency and optimal rules	4
Average partial effect estimation using double machine learning	3
Versatile differentially private learning for general loss functions	3
Unified algorithms for RL with Decision-Estimation Coefficients: PAC, reward-free, preference-based learning and beyond	3
Optimization hierarchy for fair statistical decision problems	3
Higher-order coverage errors of batching methods via Edgeworth expansions on t-statistics	3
Settling the sample complexity of model-based offline reinforcement learning	3
Berry–Esseen bounds for design-based causal inference with possibly diverging treatment levels and varying group sizes	3
Generalization error bounds of dynamic treatment regimes in penalized regression-based learning	3
Optimal heteroskedasticity testing in nonparametric regression	3
Choosing between persistent and stationary volatility	3
Sparse anomaly detection across referentials: A rank-based higher criticism approach	3
Increasing dimension asymptotics for two-way crossed mixed effect models	3
Gromov–Wasserstein distances: Entropic regularization, duality and sample complexity	3
Testing for practically significant dependencies in high dimensions via bootstrapping maxima of U-statistics	3
On blockwise and reference panel-based estimators for genetic data prediction in high dimensions	3
Optimality of approximate message passing for spiked matrix models with rotationally invariant noise	3
Metric statistics: Exploration and inference for random objects with distance profiles	3
Distributionally robust learning for multisource unsupervised domain adaptation	3
Covariance estimation under one-bit quantization	3
Empirical partially Bayes multiple testing and compound χ2 decisions	3
Low-degree hardness of detection for correlated Erdős–Rényi graphs	3
AutoRegressive approximations to nonstationary time series with inference and applications	3
Tensor factor model estimation by iterative projection	3
High-dimensional Hilbert–Schmidt linear regression with Hilbert manifold variables	3
Robust transfer learning with unreliable source data	3
Causality pursuit from heterogeneous environments via neural adversarial invariance learning	3
Variable selection, monotone likelihood ratio and group sparsity	3
Statistical-computational trade-offs in tensor PCA and related problems via communication complexity	3
Counterfactual inference in sequential experiments	3
Approximate kernel PCA: Computational versus statistical trade-off	3
A statistical framework for analyzing shape in a time series of random geometric objects	3
Online change-point detection for matrix-valued time series with latent two-way factor structure	3
Parameter estimation in nonlinear multivariate stochastic differential equations based on splitting schemes	3
Simplex quantile regression without crossing	3
Reinforcement learning for individual optimal policy from heterogeneous data	3
Multivariate root-n-consistent smoothing parameter-free matching estimators and estimators of inverse density weighted expectations	3
Sharp global convergence guarantees for iterative nonconvex optimization with random data	3
Inference for extremal regression with dependent heavy-tailed data	3
A cross-validation framework for signal denoising with applications to trend filtering, dyadic CART and beyond	3
On the statistical complexity of sample amplification	3
Complexity analysis of Bayesian learning of high-dimensional DAG models and their equivalence classes	3
Projective, sparse and learnable latent position network models	3
Dimension-free mixing times of Gibbs samplers for Bayesian hierarchical models	3
Evidence factors from multiple, possibly invalid, instrumental variables	3
Higher-order entrywise eigenvectors analysis of low-rank random matrices: Bias correction, Edgeworth expansion and bootstrap	3